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action="https://publications.waset.org/abstracts/search"> <div id="custom-search-input"> <div class="input-group"> <i class="fas fa-search"></i> <input type="text" class="search-query" name="q" placeholder="Author, Title, Abstract, Keywords" value="due-date assignment"> <input type="submit" class="btn_search" value="Search"> </div> </div> </form> </div> </div> <div class="row mt-3"> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Commenced</strong> in January 2007</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Frequency:</strong> Monthly</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Edition:</strong> International</div> </div> </div> <div class="col-sm-3"> <div class="card"> <div class="card-body"><strong>Paper Count:</strong> 219</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: due-date assignment</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">219</span> Nurse-Patient Assignment: Case of Pediatrics Department</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jihene%20Jlassi">Jihene Jlassi</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Frikha"> Ahmed Frikha</a>, <a href="https://publications.waset.org/abstracts/search?q=Wazna%20Kortli"> Wazna Kortli</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objectives of Nurse-Patient Assignment are the minimization of the overall hospital cost and the maximization of nurses ‘preferences. This paper aims to assess nurses' satisfaction related to the implementation of patient acuity tool-based assignments. So, we used an integer linear program that assigns patients to nurses while balancing nurse workloads. Then, the proposed model is applied to the Paediatrics Department at Kasserine Hospital Tunisia. Where patients need special acuities and high-level nursing skills and care. Hence, numerical results suggested that proposed nurse-patient assignment models can achieve a balanced assignment <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nurse-patient%20assignment" title="nurse-patient assignment">nurse-patient assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20model" title=" mathematical model"> mathematical model</a>, <a href="https://publications.waset.org/abstracts/search?q=logistics" title=" logistics"> logistics</a>, <a href="https://publications.waset.org/abstracts/search?q=pediatrics%20department" title=" pediatrics department"> pediatrics department</a>, <a href="https://publications.waset.org/abstracts/search?q=balanced%20assignment" title=" balanced assignment"> balanced assignment</a> </p> <a href="https://publications.waset.org/abstracts/148933/nurse-patient-assignment-case-of-pediatrics-department" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/148933.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">148</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">218</span> Seat Assignment Model for Student Admissions Process at Saudi Higher Education Institutions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Salem%20Alzahrani">Mohammed Salem Alzahrani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, student admission process is studied to optimize the assignment of vacant seats with three main objectives. Utilizing all vacant seats, satisfying all program of study admission requirements and maintaining fairness among all candidates are the three main objectives of the optimization model. Seat Assignment Method (SAM) is used to build the model and solve the optimization problem with help of Northwest Coroner Method and Least Cost Method. A closed formula is derived for applying the priority of assigning seat to candidate based on SAM. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=admission%20process%20model" title="admission process model">admission process model</a>, <a href="https://publications.waset.org/abstracts/search?q=assignment%20problem" title=" assignment problem"> assignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=Hungarian%20Method" title=" Hungarian Method"> Hungarian Method</a>, <a href="https://publications.waset.org/abstracts/search?q=Least%20Cost%20Method" title=" Least Cost Method"> Least Cost Method</a>, <a href="https://publications.waset.org/abstracts/search?q=Northwest%20Corner%20Method" title=" Northwest Corner Method"> Northwest Corner Method</a>, <a href="https://publications.waset.org/abstracts/search?q=SAM" title=" SAM"> SAM</a> </p> <a href="https://publications.waset.org/abstracts/13925/seat-assignment-model-for-student-admissions-process-at-saudi-higher-education-institutions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/13925.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">498</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">217</span> Discretization of Cuckoo Optimization Algorithm for Solving Quadratic Assignment Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Elham%20Kazemi">Elham Kazemi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Quadratic Assignment Problem (QAP) is one the combinatorial optimization problems about which research has been done in many companies for allocating some facilities to some locations. The issue of particular importance in this process is the costs of this allocation and the attempt in this problem is to minimize this group of costs. Since the QAP’s are from NP-hard problem, they cannot be solved by exact solution methods. Cuckoo Optimization Algorithm is a Meta-heuristicmethod which has higher capability to find the global optimal points. It is an algorithm which is basically raised to search a continuous space. The Quadratic Assignment Problem is the issue which can be solved in the discrete space, thus the standard arithmetic operators of Cuckoo Optimization Algorithm need to be redefined on the discrete space in order to apply the Cuckoo Optimization Algorithm on the discrete searching space. This paper represents the way of discretizing the Cuckoo optimization algorithm for solving the quadratic assignment problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Quadratic%20Assignment%20Problem%20%28QAP%29" title="Quadratic Assignment Problem (QAP)">Quadratic Assignment Problem (QAP)</a>, <a href="https://publications.waset.org/abstracts/search?q=Discrete%20Cuckoo%20Optimization%20Algorithm%20%28DCOA%29" title=" Discrete Cuckoo Optimization Algorithm (DCOA)"> Discrete Cuckoo Optimization Algorithm (DCOA)</a>, <a href="https://publications.waset.org/abstracts/search?q=meta-heuristic%20algorithms" title=" meta-heuristic algorithms"> meta-heuristic algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization%20algorithms" title=" optimization algorithms"> optimization algorithms</a> </p> <a href="https://publications.waset.org/abstracts/25249/discretization-of-cuckoo-optimization-algorithm-for-solving-quadratic-assignment-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/25249.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">517</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">216</span> A Model for Operating Rooms Scheduling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jose%20Francisco%20Ferreira%20Ribeiro">Jose Francisco Ferreira Ribeiro</a>, <a href="https://publications.waset.org/abstracts/search?q=Alexandre%20Bevilacqua%20Leoneti"> Alexandre Bevilacqua Leoneti</a>, <a href="https://publications.waset.org/abstracts/search?q=Andre%20Lucirton%20Costa"> Andre Lucirton Costa</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a mathematical model in binary variables 0/1 to make the assignment of surgical procedures to the operating rooms in a hospital. The proposed mathematical model is based on the generalized assignment problem, which maximizes the sum of preferences for the use of the operating rooms by doctors, respecting the time available in each room. The corresponding program was written in Visual Basic of Microsoft Excel, and tested to schedule surgeries at St. Lydia Hospital in Ribeirao Preto, Brazil. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=generalized%20assignment%20problem" title="generalized assignment problem">generalized assignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=logistics" title=" logistics"> logistics</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a> </p> <a href="https://publications.waset.org/abstracts/70814/a-model-for-operating-rooms-scheduling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/70814.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">292</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">215</span> Pin Count Aware Volumetric Error Detection in Arbitrary Microfluidic Bio-Chip</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Kunal%20Das">Kunal Das</a>, <a href="https://publications.waset.org/abstracts/search?q=Priya%20Sengupta"> Priya Sengupta</a>, <a href="https://publications.waset.org/abstracts/search?q=Abhishek%20K.%20Singh"> Abhishek K. Singh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Pin assignment, scheduling, routing and error detection for arbitrary biochemical protocols in Digital Microfluidic Biochip have been reported in this paper. The research work is concentrating on pin assignment for 2 or 3 droplets routing in the arbitrary biochemical protocol, scheduling and routing in m × n biochip. The volumetric error arises due to droplet split in the biochip. The volumetric error detection is also addressed using biochip AND logic gate which is known as microfluidic AND or mAND gate. The algorithm for pin assignment for m × n biochip required m+n-1 numbers of pins. The basic principle of this algorithm is that no same pin will be allowed to be placed in the same column, same row and diagonal and adjacent cells. The same pin should be placed a distance apart such that interference becomes less. A case study also reported in this paper. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=digital%20microfludic%20biochip" title="digital microfludic biochip">digital microfludic biochip</a>, <a href="https://publications.waset.org/abstracts/search?q=cross-contamination" title=" cross-contamination"> cross-contamination</a>, <a href="https://publications.waset.org/abstracts/search?q=pin%20assignment" title=" pin assignment"> pin assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=microfluidic%20AND%20gate" title=" microfluidic AND gate"> microfluidic AND gate</a> </p> <a href="https://publications.waset.org/abstracts/91627/pin-count-aware-volumetric-error-detection-in-arbitrary-microfluidic-bio-chip" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91627.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">274</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">214</span> The Application of Pareto Local Search to the Single-Objective Quadratic Assignment Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20Alsheddy">Abdullah Alsheddy</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents the employment of Pareto optimality as a strategy to help (single-objective) local search escaping local optima. Instead of local search, Pareto local search is applied to solve the quadratic assignment problem which is multi-objectivized by adding a helper objective. The additional objective is defined as a function of the primary one with augmented penalties that are dynamically updated. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=Pareto%20optimization" title="Pareto optimization">Pareto optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=multi-objectivization" title=" multi-objectivization"> multi-objectivization</a>, <a href="https://publications.waset.org/abstracts/search?q=quadratic%20assignment%20problem" title=" quadratic assignment problem"> quadratic assignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=local%20search" title=" local search"> local search</a> </p> <a href="https://publications.waset.org/abstracts/9877/the-application-of-pareto-local-search-to-the-single-objective-quadratic-assignment-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/9877.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">466</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">213</span> Solving Process Planning, Weighted Earliest Due Date Scheduling and Weighted Due Date Assignment Using Simulated Annealing and Evolutionary Strategies</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halil%20Ibrahim%20Demir">Halil Ibrahim Demir</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdullah%20Hulusi%20Kokcam"> Abdullah Hulusi Kokcam</a>, <a href="https://publications.waset.org/abstracts/search?q=Fuat%20Simsir"> Fuat Simsir</a>, <a href="https://publications.waset.org/abstracts/search?q=%C3%96zer%20Uygun"> Özer Uygun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditionally, three important manufacturing functions which are process planning, scheduling and due-date assignment are performed sequentially and separately. Although there are numerous works on the integration of process planning and scheduling and plenty of works focusing on scheduling with due date assignment, there are only a few works on integrated process planning, scheduling and due-date assignment. Although due-dates are determined without taking into account of weights of the customers in the literature, here weighted due-date assignment is employed to get better performance. Jobs are scheduled according to weighted earliest due date dispatching rule and due dates are determined according to some popular due date assignment methods by taking into account of the weights of each job. Simulated Annealing, Evolutionary Strategies, Random Search, hybrid of Random Search and Simulated Annealing, and hybrid of Random Search and Evolutionary Strategies, are applied as solution techniques. Three important manufacturing functions are integrated step-by-step and higher integration levels are found better. Search meta-heuristics are found to be very useful while improving performance measure. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=process%20planning" title="process planning">process planning</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20scheduling" title=" weighted scheduling"> weighted scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20due-date%20assignment" title=" weighted due-date assignment"> weighted due-date assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20strategies" title=" evolutionary strategies"> evolutionary strategies</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20searches" title=" hybrid searches"> hybrid searches</a> </p> <a href="https://publications.waset.org/abstracts/67706/solving-process-planning-weighted-earliest-due-date-scheduling-and-weighted-due-date-assignment-using-simulated-annealing-and-evolutionary-strategies" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/67706.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">462</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">212</span> Hybrid Approach for the Min-Interference Frequency Assignment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=F.%20Debbat">F. Debbat</a>, <a href="https://publications.waset.org/abstracts/search?q=F.%20T.%20Bendimerad"> F. T. Bendimerad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The efficient frequency assignment for radio communications becomes more and more crucial when developing new information technologies and their applications. It is consists in defining an assignment of frequencies to radio links, to be established between base stations and mobile transmitters. Separation of the frequencies assigned is necessary to avoid interference. However, unnecessary separation causes an excess requirement for spectrum, the cost of which may be very high. This problem is NP-hard problem which cannot be solved by conventional optimization algorithms. It is therefore necessary to use metaheuristic methods to solve it. This paper proposes Hybrid approach based on simulated annealing (SA) and Tabu Search (TS) methods to solve this problem. Computational results, obtained on a number of standard problem instances, testify the effectiveness of the proposed approach. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cellular%20mobile%20communication" title="cellular mobile communication">cellular mobile communication</a>, <a href="https://publications.waset.org/abstracts/search?q=frequency%20assignment%20problem" title=" frequency assignment problem"> frequency assignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=tabu%20search" title=" tabu search"> tabu search</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a> </p> <a href="https://publications.waset.org/abstracts/14250/hybrid-approach-for-the-min-interference-frequency-assignment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/14250.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">385</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">211</span> Solving Process Planning and Scheduling with Number of Operation Plus Processing Time Due-Date Assignment Concurrently Using a Genetic Search</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halil%20Ibrahim%20Demir">Halil Ibrahim Demir</a>, <a href="https://publications.waset.org/abstracts/search?q=Alper%20Goksu"> Alper Goksu</a>, <a href="https://publications.waset.org/abstracts/search?q=Onur%20Canpolat"> Onur Canpolat</a>, <a href="https://publications.waset.org/abstracts/search?q=Caner%20Erden"> Caner Erden</a>, <a href="https://publications.waset.org/abstracts/search?q=Melek%20Nur"> Melek Nur</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditionally process planning, scheduling and due date assignment are performed sequentially and separately. High interrelation between these functions makes integration very useful. Although there are numerous works on integrated process planning and scheduling and many works on scheduling with due date assignment, there are only a few works on the integration of these three functions. Here we tested the different integration levels of these three functions and found a fully integrated version as the best. We applied genetic search and random search and genetic search was found better compared to the random search. We penalized all earliness, tardiness and due date related costs. Since all these three terms are all undesired, it is better to penalize all of them. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=process%20planning" title="process planning">process planning</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=due-date%20assignment" title=" due-date assignment"> due-date assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20search" title=" random search"> random search</a> </p> <a href="https://publications.waset.org/abstracts/68612/solving-process-planning-and-scheduling-with-number-of-operation-plus-processing-time-due-date-assignment-concurrently-using-a-genetic-search" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/68612.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">375</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">210</span> Integrating Process Planning, WMS Dispatching, and WPPW Weighted Due Date Assignment Using a Genetic Algorithm</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halil%20Ibrahim%20Demir">Halil Ibrahim Demir</a>, <a href="https://publications.waset.org/abstracts/search?q=Tar%C4%B1k%20Cakar"> Tarık Cakar</a>, <a href="https://publications.waset.org/abstracts/search?q=Ibrahim%20Cil"> Ibrahim Cil</a>, <a href="https://publications.waset.org/abstracts/search?q=Muharrem%20Dugenci"> Muharrem Dugenci</a>, <a href="https://publications.waset.org/abstracts/search?q=Caner%20Erden"> Caner Erden</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Conventionally, process planning, scheduling, and due-date assignment functions are performed separately and sequentially. The interdependence of these functions requires integration. Although integrated process planning and scheduling, and scheduling with due date assignment problems are popular research topics, only a few works address the integration of these three functions. This work focuses on the integration of process planning, WMS scheduling, and WPPW due date assignment. Another novelty of this work is the use of a weighted due date assignment. In the literature, due dates are generally assigned without considering the importance of customers. However, in this study, more important customers get closer due dates. Typically, only tardiness is punished, but the JIT philosophy punishes both earliness and tardiness. In this study, all weighted earliness, tardiness, and due date related costs are penalized. As no customer desires distant due dates, such distant due dates should be penalized. In this study, various levels of integration of these three functions are tested and genetic search and random search are compared both with each other and with ordinary solutions. Higher integration levels are superior, while search is always useful. Genetic searches outperformed random searches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=process%20planning" title="process planning">process planning</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20scheduling" title=" weighted scheduling"> weighted scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20due-date%20assignment" title=" weighted due-date assignment"> weighted due-date assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=random%20search" title=" random search"> random search</a> </p> <a href="https://publications.waset.org/abstracts/51544/integrating-process-planning-wms-dispatching-and-wppw-weighted-due-date-assignment-using-a-genetic-algorithm" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51544.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">394</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">209</span> Optimizing Network Latency with Fast Path Assignment for Incoming Flows</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qing%20Lyu">Qing Lyu</a>, <a href="https://publications.waset.org/abstracts/search?q=Hang%20Zhu"> Hang Zhu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Various flows in the network require to go through different types of middlebox. The improper placement of network middlebox and path assignment for flows could greatly increase the network latency and also decrease the performance of network. Minimizing the total end to end latency of all the ows requires to assign path for the incoming flows. In this paper, the flow path assignment problem in regard to the placement of various kinds of middlebox is studied. The flow path assignment problem is formulated to a linear programming problem, which is very time consuming. On the other hand, a naive greedy algorithm is studied. Which is very fast but causes much more latency than the linear programming algorithm. At last, the paper presents a heuristic algorithm named FPA, which takes bottleneck link information and estimated bandwidth occupancy into consideration, and achieves near optimal latency in much less time. Evaluation results validate the effectiveness of the proposed algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flow%20path" title="flow path">flow path</a>, <a href="https://publications.waset.org/abstracts/search?q=latency" title=" latency"> latency</a>, <a href="https://publications.waset.org/abstracts/search?q=middlebox" title=" middlebox"> middlebox</a>, <a href="https://publications.waset.org/abstracts/search?q=network" title=" network"> network</a> </p> <a href="https://publications.waset.org/abstracts/103177/optimizing-network-latency-with-fast-path-assignment-for-incoming-flows" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/103177.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">207</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">208</span> The Analysis of Split Graphs in Social Networks Based on the k-Cardinality Assignment Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ivan%20Belik">Ivan Belik</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In terms of social networks split graphs correspond to the variety of interpersonal and intergroup relations. In this paper we analyse the interaction between the cliques (socially strong and trusty groups) and the independent sets (fragmented and non-connected groups of people) as the basic components of any split graph. Based on the Semi-Lagrangean relaxation for the k-cardinality assignment problem we show the way of how to minimize the socially risky interactions between the cliques and the independent sets within the social network. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cliques" title="cliques">cliques</a>, <a href="https://publications.waset.org/abstracts/search?q=independent%20sets" title=" independent sets"> independent sets</a>, <a href="https://publications.waset.org/abstracts/search?q=k-cardinality%20assignment" title=" k-cardinality assignment"> k-cardinality assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=social%20networks" title=" social networks"> social networks</a>, <a href="https://publications.waset.org/abstracts/search?q=split%20graphs" title=" split graphs"> split graphs</a> </p> <a href="https://publications.waset.org/abstracts/15143/the-analysis-of-split-graphs-in-social-networks-based-on-the-k-cardinality-assignment-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/15143.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">320</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">207</span> A Priority Based Imbalanced Time Minimization Assignment Problem: An Iterative Approach</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ekta%20Jain">Ekta Jain</a>, <a href="https://publications.waset.org/abstracts/search?q=Kalpana%20Dahiya"> Kalpana Dahiya</a>, <a href="https://publications.waset.org/abstracts/search?q=Vanita%20Verma"> Vanita Verma</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper discusses a priority based imbalanced time minimization assignment problem dealing with the allocation of n jobs to m < n persons in which the project is carried out in two stages, viz. Stage-I and Stage-II. Stage-I consists of n1 ( < m) primary jobs and Stage-II consists of remaining (n-n1) secondary jobs which are commenced only after primary jobs are finished. Each job is to be allocated to exactly one person, and each person has to do at least one job. It is assumed that nature of the Stage-I jobs is such that one person can do exactly one primary job whereas a person can do more than one secondary job in Stage-II. In a particular stage, all persons start doing the jobs simultaneously, but if a person is doing more than one job, he does them one after the other in any order. The aim of the proposed study is to find the feasible assignment which minimizes the total time for the two stage execution of the project. For this, an iterative algorithm is proposed, which at each iteration, solves a constrained imbalanced time minimization assignment problem to generate a pair of Stage-I and Stage-II times. For solving this constrained problem, an algorithm is developed in the current paper. Later, alternate combinations based method to solve the priority based imbalanced problem is also discussed and a comparative study is carried out. Numerical illustrations are provided in support of the theory. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assignment" title="assignment">assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=imbalanced" title=" imbalanced"> imbalanced</a>, <a href="https://publications.waset.org/abstracts/search?q=priority" title=" priority"> priority</a>, <a href="https://publications.waset.org/abstracts/search?q=time%20minimization" title=" time minimization"> time minimization</a> </p> <a href="https://publications.waset.org/abstracts/75198/a-priority-based-imbalanced-time-minimization-assignment-problem-an-iterative-approach" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75198.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">234</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">206</span> A Study of Traffic Assignment Algorithms</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abdelfetah%20Laouzai">Abdelfetah Laouzai</a>, <a href="https://publications.waset.org/abstracts/search?q=Rachid%20Ouafi"> Rachid Ouafi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In a traffic network, users usually choose their way so that it reduces their travel time between pairs origin-destination. This behavior might seem selfish as it produces congestions in different parts of the network. The traffic assignment problem (TAP) models the interactions between congestion and user travel decisions to obtain vehicles flows over each axis of the traffic network. The resolution methods of TAP serve as a tool allows predicting users’ distribution, identifying congesting points and affecting the travelers’ behavior in the choice of their route in the network following dynamic data. In this article, we will present a review about specific resolution approach of TAP. A comparative analysis is carried out on those approaches so that it highlights the characteristics, advantages and disadvantages of each. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=network%20traffic" title="network traffic">network traffic</a>, <a href="https://publications.waset.org/abstracts/search?q=travel%20decisions" title=" travel decisions"> travel decisions</a>, <a href="https://publications.waset.org/abstracts/search?q=approaches" title=" approaches"> approaches</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20assignment" title=" traffic assignment"> traffic assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=flows" title=" flows"> flows</a> </p> <a href="https://publications.waset.org/abstracts/37867/a-study-of-traffic-assignment-algorithms" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/37867.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">474</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">205</span> Public Transport Assignment at Adama City</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Selamawit%20Mulubrhan%20Gidey">Selamawit Mulubrhan Gidey</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Adama city, having an area of 29.86 km2, is one of the main cities in Ethiopia experiencing rapid growth in business and construction activities which in turn with an increasing number of vehicles at an alarming rate. For this reason, currently, there is an attempt to develop public transport assignment modeling in the city. Still, there is a huge gap in developing public transport assignments along the road segments of the city with operational and safety performance due to high traffic volume. Thus, the introduction of public transport assignment modeling in Adama City can have a massive impact on the road safety and capacity problem in the city. City transport modeling is important in city transportation planning, particularly in overcoming existing transportation problems such as traffic congestion. In this study, the Adama City transportation model was developed using the PTV VISUM software, whose transportation modeling is based on the four-step model of transportation. Based on the traffic volume data fed and simulated, the result of the study shows that the developed model has better reliability in representing the traffic congestion conditions in Adama city, and the simulation clearly indicates the level of congestion of each route selected and thus, the city road administrative office can take managerial decisions on public transport assignment so as to overcome traffic congestion executed along the selected routes. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=trip%20modelling" title="trip modelling">trip modelling</a>, <a href="https://publications.waset.org/abstracts/search?q=PTV%20VISUM" title=" PTV VISUM"> PTV VISUM</a>, <a href="https://publications.waset.org/abstracts/search?q=public%20transport%20assignment" title=" public transport assignment"> public transport assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=congestion" title=" congestion"> congestion</a> </p> <a href="https://publications.waset.org/abstracts/187078/public-transport-assignment-at-adama-city" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/187078.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">43</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">204</span> A 15 Minute-Based Approach for Berth Allocation and Quay Crane Assignment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hoi-Lam%20Ma">Hoi-Lam Ma</a>, <a href="https://publications.waset.org/abstracts/search?q=Sai-Ho%20Chung"> Sai-Ho Chung</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In traditional integrated berth allocation with quay crane assignment models, time dimension is usually assumed in hourly based. However, nowadays, transshipment becomes the main business to many container terminals, especially in Southeast Asia (e.g. Hong Kong and Singapore). In these terminals, vessel arrivals are usually very frequent with small handling volume and very short staying time. Therefore, the traditional hourly-based modeling approach may cause significant berth and quay crane idling, and consequently cannot meet their practical needs. In this connection, a 15-minute-based modeling approach is requested by industrial practitioners. Accordingly, a Three-level Genetic Algorithm (3LGA) with Quay Crane (QC) shifting heuristics is designed to fulfill the research gap. The objective function here is to minimize the total service time. Preliminary numerical results show that the proposed 15-minute-based approach can reduce the berth and QC idling significantly. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=transshipment" title="transshipment">transshipment</a>, <a href="https://publications.waset.org/abstracts/search?q=integrated%20berth%20allocation" title=" integrated berth allocation"> integrated berth allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=variable-in-time%20quay%20crane%20assignment" title=" variable-in-time quay crane assignment"> variable-in-time quay crane assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=quay%20crane%20assignment" title=" quay crane assignment"> quay crane assignment</a> </p> <a href="https://publications.waset.org/abstracts/95988/a-15-minute-based-approach-for-berth-allocation-and-quay-crane-assignment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/95988.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">169</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">203</span> Spectrum Assignment Algorithms in Optical Networks with Protection</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qusay%20Alghazali">Qusay Alghazali</a>, <a href="https://publications.waset.org/abstracts/search?q=Tibor%20Cinkler"> Tibor Cinkler</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdulhalim%20Fayad"> Abdulhalim Fayad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In modern optical networks, the flex grid spectrum usage is most widespread, where higher bit rate streams get larger spectrum slices while lower bit rate traffic streams get smaller spectrum slices. To our practice, under the ITU-T recommendation, G.694.1, spectrum slices of 50, 75, and 100 GHz are being used with central frequency at 193.1 THz. However, when these spectrum slices are not sufficient, multiple spectrum slices can use either one next to another or anywhere in the optical wavelength. In this paper, we propose the analysis of the wavelength assignment problem. We compare different algorithms for this spectrum assignment with and without protection. As a reference for comparisons, we concluded that the Integer Linear Programming (ILP) provides the global optimum for all cases. The most scalable algorithm is the greedy one, which yields results in subsequent ranges even for more significant network instances. The algorithms’ benchmark implemented using the LEMON C++ optimization library and simulation runs based on a minimum number of spectrum slices assigned to lightpaths and their execution time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=spectrum%20assignment" title="spectrum assignment">spectrum assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=integer%20linear%20programming" title=" integer linear programming"> integer linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=greedy%20algorithm" title=" greedy algorithm"> greedy algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=international%20telecommunication%20union" title=" international telecommunication union"> international telecommunication union</a>, <a href="https://publications.waset.org/abstracts/search?q=library%20for%20efficient%20modeling%20and%20optimization%20in%20networks" title=" library for efficient modeling and optimization in networks"> library for efficient modeling and optimization in networks</a> </p> <a href="https://publications.waset.org/abstracts/136766/spectrum-assignment-algorithms-in-optical-networks-with-protection" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/136766.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">169</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">202</span> Improving the Run Times of Existing and Historical Demand Models Using Simple Python Scripting</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Abhijeet%20Ostawal">Abhijeet Ostawal</a>, <a href="https://publications.waset.org/abstracts/search?q=Parmjit%20Lall"> Parmjit Lall</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The run times for a large strategic model that we were managing had become too long leading to delays in project delivery, increased costs and loss in productivity. Software developers are continuously working towards developing more efficient tools by changing their algorithms and processes. The issue faced by our team was how do you apply the latest technologies on validated existing models which are based on much older versions of software that do not have the latest software capabilities. The multi-model transport model that we had could only be run in sequential assignment order. Recent upgrades to the software now allowed the assignment to be run in parallel, a concept called parallelization. Parallelization is a Python script working only within the latest version of the software. A full model transfer to the latest version was not possible due to time, budget and the potential changes in trip assignment. This article is to show the method to adapt and update the Python script in such a way that it can be used in older software versions by calling the latest version and then recalling the old version for assignment model without affecting the results. Through a process of trial-and-error run time savings of up to 30-40% have been achieved. Assignment results were maintained within the older version and through this learning process we’ve applied this methodology to other even older versions of the software resulting in huge time savings, more productivity and efficiency for both client and consultant. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=model%20run%20time" title="model run time">model run time</a>, <a href="https://publications.waset.org/abstracts/search?q=demand%20model" title=" demand model"> demand model</a>, <a href="https://publications.waset.org/abstracts/search?q=parallelisation" title=" parallelisation"> parallelisation</a>, <a href="https://publications.waset.org/abstracts/search?q=python%20scripting" title=" python scripting"> python scripting</a> </p> <a href="https://publications.waset.org/abstracts/149033/improving-the-run-times-of-existing-and-historical-demand-models-using-simple-python-scripting" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/149033.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">118</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">201</span> Multichannel Scheme under Fairness Environment for Cognitive Radio Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hans%20Marquez%20Ramos">Hans Marquez Ramos</a>, <a href="https://publications.waset.org/abstracts/search?q=Cesar%20Hernandez"> Cesar Hernandez</a>, <a href="https://publications.waset.org/abstracts/search?q=Ingrid%20P%C3%A1ez"> Ingrid Páez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper develops a multiple channel assignment model, which allows to take advantage in most efficient way, spectrum opportunities in cognitive radio networks. Developed scheme allows make several available and frequency adjacent channel assignments, which require a bigger wide band, under an equality environment. The hybrid assignment model it is made by to algorithms, one who makes the ranking and select available frequency channels and the other one in charge of establishing an equality criteria, in order to not restrict spectrum opportunities for all other secondary users who wish to make transmissions. Measurements made were done for average bandwidth, average delay, as well fairness computation for several channel assignment. Reached results were evaluated with experimental spectrum occupational data from GSM frequency band captured. Developed model, shows evidence of improvement in spectrum opportunity use and a wider average transmit bandwidth for each secondary user, maintaining equality criteria in channel assignment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bandwidth" title="bandwidth">bandwidth</a>, <a href="https://publications.waset.org/abstracts/search?q=fairness" title=" fairness"> fairness</a>, <a href="https://publications.waset.org/abstracts/search?q=multichannel" title=" multichannel"> multichannel</a>, <a href="https://publications.waset.org/abstracts/search?q=secondary%20users" title=" secondary users"> secondary users</a> </p> <a href="https://publications.waset.org/abstracts/32694/multichannel-scheme-under-fairness-environment-for-cognitive-radio-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/32694.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">504</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">200</span> Solving Weighted Number of Operation Plus Processing Time Due-Date Assignment, Weighted Scheduling and Process Planning Integration Problem Using Genetic and Simulated Annealing Search Methods</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Halil%20Ibrahim%20Demir">Halil Ibrahim Demir</a>, <a href="https://publications.waset.org/abstracts/search?q=Caner%20Erden"> Caner Erden</a>, <a href="https://publications.waset.org/abstracts/search?q=Mumtaz%20Ipek"> Mumtaz Ipek</a>, <a href="https://publications.waset.org/abstracts/search?q=Ozer%20Uygun"> Ozer Uygun</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Traditionally, the three important manufacturing functions, which are process planning, scheduling and due-date assignment, are performed separately and sequentially. For couple of decades, hundreds of studies are done on integrated process planning and scheduling problems and numerous researches are performed on scheduling with due date assignment problem, but unfortunately the integration of these three important functions are not adequately addressed. Here, the integration of these three important functions is studied by using genetic, random-genetic hybrid, simulated annealing, random-simulated annealing hybrid and random search techniques. As well, the importance of the integration of these three functions and the power of meta-heuristics and of hybrid heuristics are studied. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=process%20planning" title="process planning">process planning</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20scheduling" title=" weighted scheduling"> weighted scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=weighted%20due-date%20assignment" title=" weighted due-date assignment"> weighted due-date assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20search" title=" genetic search"> genetic search</a>, <a href="https://publications.waset.org/abstracts/search?q=simulated%20annealing" title=" simulated annealing"> simulated annealing</a>, <a href="https://publications.waset.org/abstracts/search?q=hybrid%20meta-heuristics" title=" hybrid meta-heuristics"> hybrid meta-heuristics</a> </p> <a href="https://publications.waset.org/abstracts/57629/solving-weighted-number-of-operation-plus-processing-time-due-date-assignment-weighted-scheduling-and-process-planning-integration-problem-using-genetic-and-simulated-annealing-search-methods" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/57629.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">469</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">199</span> A Polynomial Time Clustering Algorithm for Solving the Assignment Problem in the Vehicle Routing Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lydia%20Wahid">Lydia Wahid</a>, <a href="https://publications.waset.org/abstracts/search?q=Mona%20F.%20Ahmed"> Mona F. Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Nevin%20Darwish"> Nevin Darwish</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The vehicle routing problem (VRP) consists of a group of customers that needs to be served. Each customer has a certain demand of goods. A central depot having a fleet of vehicles is responsible for supplying the customers with their demands. The problem is composed of two subproblems: The first subproblem is an assignment problem where the number of vehicles that will be used as well as the customers assigned to each vehicle are determined. The second subproblem is the routing problem in which for each vehicle having a number of customers assigned to it, the order of visits of the customers is determined. Optimal number of vehicles, as well as optimal total distance, should be achieved. In this paper, an approach for solving the first subproblem (the assignment problem) is presented. In the approach, a clustering algorithm is proposed for finding the optimal number of vehicles by grouping the customers into clusters where each cluster is visited by one vehicle. Finding the optimal number of clusters is NP-hard. This work presents a polynomial time clustering algorithm for finding the optimal number of clusters and solving the assignment problem. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=vehicle%20routing%20problems" title="vehicle routing problems">vehicle routing problems</a>, <a href="https://publications.waset.org/abstracts/search?q=clustering%20algorithms" title=" clustering algorithms"> clustering algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=Clarke%20and%20Wright%20Saving%20Method" title=" Clarke and Wright Saving Method"> Clarke and Wright Saving Method</a>, <a href="https://publications.waset.org/abstracts/search?q=agglomerative%20hierarchical%20clustering" title=" agglomerative hierarchical clustering"> agglomerative hierarchical clustering</a> </p> <a href="https://publications.waset.org/abstracts/85552/a-polynomial-time-clustering-algorithm-for-solving-the-assignment-problem-in-the-vehicle-routing-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/85552.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">393</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">198</span> Racial Bias by Prosecutors: Evidence from Random Assignment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=CarlyWill%20Sloan">CarlyWill Sloan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Racial disparities in criminal justice outcomes are well-documented. However, there is little evidence on the extent to which racial bias by prosecutors is responsible for these disparities. This paper tests for racial bias in conviction by prosecutors. To identify effects, this paper leverages as good as random variation in prosecutor race using detailed administrative data on the case assignment process and case outcomes in New York County, New York. This paper shows that the assignment of an opposite-race prosecutor leads to a 5 percentage point (~ 8 percent) increase in the likelihood of conviction for property crimes. There is no evidence of effects for other types of crimes. Additional results indicate decreased dismissals by opposite-race prosecutors likely drive my property crime estimates. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=criminal%20justice" title="criminal justice">criminal justice</a>, <a href="https://publications.waset.org/abstracts/search?q=discrimination" title=" discrimination"> discrimination</a>, <a href="https://publications.waset.org/abstracts/search?q=prosecutors" title=" prosecutors"> prosecutors</a>, <a href="https://publications.waset.org/abstracts/search?q=racial%20disparities" title=" racial disparities"> racial disparities</a> </p> <a href="https://publications.waset.org/abstracts/108678/racial-bias-by-prosecutors-evidence-from-random-assignment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108678.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">191</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">197</span> Implementation of a Program of Orientation for Travel Nursing Staff Based on Nurse-Identified Learning Needs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Olga%20C.%20Rodrigue">Olga C. Rodrigue</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Long-term care and skilled nursing facilities experience ebbs and flows of nursing staffing, a problem compounded by the perception of the facilities as undesirable workplaces and competition for staff from other healthcare entities. Travel nurses are contracted to fill staffing needs due to increased admissions, increased and unexpected attrition of nurses, or facility expansion of services. Prior to beginning the contracted assignment, the travel nurse must meet industry, company, and regulatory requirements (The Joint Commission and CMS) for skills and knowledge. Travel nurses, however, inconsistently receive the pre-assignment orientation needed to work at the contracted facility, if any information is given at all. When performance expectations are not met, travel nurses may subsequently choose to leave the position without completing the terms of the contract, and some facilities may choose to terminate the contract prior to the expected end date. The overarching goal of the Doctor of Nursing Practice evidence-based practice improvement project is to provide travel nurses with the basic and necessary information to prepare them to begin a long-term and skilled nursing assignment. The project involves the identification of travel nurse learning needs through a survey and the development and provision of web-based learning modules to address those needs prior to arrival for a long-term and skilled nursing assignment. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nurse%20staffing" title="nurse staffing">nurse staffing</a>, <a href="https://publications.waset.org/abstracts/search?q=travel%20nurse" title=" travel nurse"> travel nurse</a>, <a href="https://publications.waset.org/abstracts/search?q=travel%20staff" title=" travel staff"> travel staff</a>, <a href="https://publications.waset.org/abstracts/search?q=contract%20staff" title=" contract staff"> contract staff</a>, <a href="https://publications.waset.org/abstracts/search?q=contracted%20assignment" title=" contracted assignment"> contracted assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=long-term%20care" title=" long-term care"> long-term care</a>, <a href="https://publications.waset.org/abstracts/search?q=skilled%20nursing" title=" skilled nursing"> skilled nursing</a>, <a href="https://publications.waset.org/abstracts/search?q=onboarding" title=" onboarding"> onboarding</a>, <a href="https://publications.waset.org/abstracts/search?q=orientation" title=" orientation"> orientation</a>, <a href="https://publications.waset.org/abstracts/search?q=staff%20development" title=" staff development"> staff development</a>, <a href="https://publications.waset.org/abstracts/search?q=supplemental%20staff" title=" supplemental staff"> supplemental staff</a> </p> <a href="https://publications.waset.org/abstracts/151391/implementation-of-a-program-of-orientation-for-travel-nursing-staff-based-on-nurse-identified-learning-needs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/151391.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">168</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">196</span> Storage Assignment Strategies to Reduce Manual Picking Errors with an Emphasis on an Ageing Workforce</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Heiko%20Diefenbach">Heiko Diefenbach</a>, <a href="https://publications.waset.org/abstracts/search?q=Christoph%20H.%20Glock"> Christoph H. Glock</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Order picking, i.e., the order-based retrieval of items in a warehouse, is an important time- and cost-intensive process for many logistic systems. Despite the ongoing trend of automation, most order picking systems are still manual picker-to-parts systems, where human pickers walk through the warehouse to collect ordered items. Human work in warehouses is not free from errors, and order pickers may at times pick the wrong or the incorrect number of items. Errors can cause additional costs and significant correction efforts. Moreover, age might increase a person’s likelihood to make mistakes. Hence, the negative impact of picking errors might increase for an aging workforce currently witnessed in many regions globally. A significant amount of research has focused on making order picking systems more efficient. Among other factors, storage assignment, i.e., the assignment of items to storage locations (e.g., shelves) within the warehouse, has been subject to optimization. Usually, the objective is to assign items to storage locations such that order picking times are minimized. Surprisingly, there is a lack of research concerned with picking errors and respective prevention approaches. This paper hypothesize that the storage assignment of items can affect the probability of pick errors. For example, storing similar-looking items apart from one other might reduce confusion. Moreover, storing items that are hard to count or require a lot of counting at easy-to-access and easy-to-comprehend self heights might reduce the probability to pick the wrong number of items. Based on this hypothesis, the paper discusses how to incorporate error-prevention measures into mathematical models for storage assignment optimization. Various approaches with respective benefits and shortcomings are presented and mathematically modeled. To investigate the newly developed models further, they are compared to conventional storage assignment strategies in a computational study. The study specifically investigates how the importance of error prevention increases with pickers being more prone to errors due to age, for example. The results suggest that considering error-prevention measures for storage assignment can reduce error probabilities with only minor decreases in picking efficiency. The results might be especially relevant for an aging workforce. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=an%20aging%20workforce" title="an aging workforce">an aging workforce</a>, <a href="https://publications.waset.org/abstracts/search?q=error%20prevention" title=" error prevention"> error prevention</a>, <a href="https://publications.waset.org/abstracts/search?q=order%20picking" title=" order picking"> order picking</a>, <a href="https://publications.waset.org/abstracts/search?q=storage%20assignment" title=" storage assignment"> storage assignment</a> </p> <a href="https://publications.waset.org/abstracts/142787/storage-assignment-strategies-to-reduce-manual-picking-errors-with-an-emphasis-on-an-ageing-workforce" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/142787.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">204</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">195</span> Assignment of Airlines Technical Members under Disruption</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Walid%20Moudani">Walid Moudani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Crew Reserve Assignment Problem (CRAP) considers the assignment of the crew members to a set of reserve activities covering all the scheduled flights in order to ensure a continuous plan so that operations costs are minimized while its solution must meet hard constraints resulting from the safety regulations of Civil Aviation as well as from the airlines internal agreements. The problem considered in this study is of highest interest for airlines and may have important consequences on the service quality and on the economic return of the operations. In this communication, a new mathematical formulation for the CRAP is proposed which takes into account the regulations and the internal agreements. While current solutions make use of Artificial Intelligence techniques run on main frame computers, a low cost approach is proposed to provide on-line efficient solutions to face perturbed operating conditions. The proposed solution method uses a dynamic programming approach for the duties scheduling problem and when applied to the case of a medium airline while providing efficient solutions, shows good potential acceptability by the operations staff. This optimization scheme can then be considered as the core of an on-line Decision Support System for crew reserve assignment operations management. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=airlines%20operations%20management" title="airlines operations management">airlines operations management</a>, <a href="https://publications.waset.org/abstracts/search?q=combinatorial%20optimization" title=" combinatorial optimization"> combinatorial optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20programming" title=" dynamic programming"> dynamic programming</a>, <a href="https://publications.waset.org/abstracts/search?q=crew%20scheduling" title=" crew scheduling"> crew scheduling</a> </p> <a href="https://publications.waset.org/abstracts/6807/assignment-of-airlines-technical-members-under-disruption" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/6807.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">354</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">194</span> Resource Allocation and Task Scheduling with Skill Level and Time Bound Constraints</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Salam%20Saudagar">Salam Saudagar</a>, <a href="https://publications.waset.org/abstracts/search?q=Ankit%20Kamboj"> Ankit Kamboj</a>, <a href="https://publications.waset.org/abstracts/search?q=Niraj%20Mohan"> Niraj Mohan</a>, <a href="https://publications.waset.org/abstracts/search?q=Satgounda%20Patil"> Satgounda Patil</a>, <a href="https://publications.waset.org/abstracts/search?q=Nilesh%20Powar"> Nilesh Powar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Task Assignment and Scheduling is a challenging Operations Research problem when there is a limited number of resources and comparatively higher number of tasks. The Cost Management team at Cummins needs to assign tasks based on a deadline and must prioritize some of the tasks as per business requirements. Moreover, there is a constraint on the resources that assignment of tasks should be done based on an individual skill level, that may vary for different tasks. Another constraint is for scheduling the tasks that should be evenly distributed in terms of number of working hours, which adds further complexity to this problem. The proposed greedy approach to solve assignment and scheduling problem first assigns the task based on management priority and then by the closest deadline. This is followed by an iterative selection of an available resource with the least allocated total working hours for a task, i.e. finding the local optimal choice for each task with the goal of determining the global optimum. The greedy approach task allocation is compared with a variant of Hungarian Algorithm, and it is observed that the proposed approach gives an equal allocation of working hours among the resources. The comparative study of the proposed approach is also done with manual task allocation and it is noted that the visibility of the task timeline has increased from 2 months to 6 months. An interactive dashboard app is created for the greedy assignment and scheduling approach and the tasks with more than 2 months horizon that were waiting in a queue without a delivery date initially are now analyzed effectively by the business with expected timelines for completion. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assignment" title="assignment">assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=deadline" title=" deadline"> deadline</a>, <a href="https://publications.waset.org/abstracts/search?q=greedy%20approach" title=" greedy approach"> greedy approach</a>, <a href="https://publications.waset.org/abstracts/search?q=Hungarian%20algorithm" title=" Hungarian algorithm"> Hungarian algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=operations%20research" title=" operations research"> operations research</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a> </p> <a href="https://publications.waset.org/abstracts/128820/resource-allocation-and-task-scheduling-with-skill-level-and-time-bound-constraints" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/128820.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">147</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">193</span> Method of Parameter Calibration for Error Term in Stochastic User Equilibrium Traffic Assignment Model</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xiang%20Zhang">Xiang Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=David%20Rey"> David Rey</a>, <a href="https://publications.waset.org/abstracts/search?q=S.%20Travis%20Waller"> S. Travis Waller</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Stochastic User Equilibrium (SUE) model is a widely used traffic assignment model in transportation planning, which is regarded more advanced than Deterministic User Equilibrium (DUE) model. However, a problem exists that the performance of the SUE model depends on its error term parameter. The objective of this paper is to propose a systematic method of determining the appropriate error term parameter value for the SUE model. First, the significance of the parameter is explored through a numerical example. Second, the parameter calibration method is developed based on the Logit-based route choice model. The calibration process is realized through multiple nonlinear regression, using sequential quadratic programming combined with least square method. Finally, case analysis is conducted to demonstrate the application of the calibration process and validate the better performance of the SUE model calibrated by the proposed method compared to the SUE models under other parameter values and the DUE model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=parameter%20calibration" title="parameter calibration">parameter calibration</a>, <a href="https://publications.waset.org/abstracts/search?q=sequential%20quadratic%20programming" title=" sequential quadratic programming"> sequential quadratic programming</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20user%20equilibrium" title=" stochastic user equilibrium"> stochastic user equilibrium</a>, <a href="https://publications.waset.org/abstracts/search?q=traffic%20assignment" title=" traffic assignment"> traffic assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=transportation%20planning" title=" transportation planning"> transportation planning</a> </p> <a href="https://publications.waset.org/abstracts/17091/method-of-parameter-calibration-for-error-term-in-stochastic-user-equilibrium-traffic-assignment-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/17091.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">299</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">192</span> E Learning/Teaching and the Impact on Student Performance at the Postgraduate Level </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Charles%20Lemckert">Charles Lemckert</a> </p> <p class="card-text"><strong>Abstract:</strong></p> E-Learning and E-Teaching can mean many things to different people. For some, the implication is that all material must be delivered in an E way, while for others it only forms part of the learning/teaching process, and (unfortunately) for some it is considered too much work. However, just look around and you will see all generations learning using E devices. In this study we used different forms of teaching, including E, to look at how students responded to set activities and how they performed academically. The particular context was set around a postgraduate university course where students were either present at a face-to-face intensive workshop (on water treatment plant design) or where they were not. For the latter, students needed to make sole use of E media. It is relevant to note that even though some were at the face-to-face class, they were still exposed to E material as the lecturer did use PC projections. Additionally, some also accessed the associate E material (pdf slides and video recordings) to assist their required activities. Analysis of the student performance, in their set assignment, showed that the actual form of delivery did not affect the student performance. This is because, in the end, all the students had access to the recorded/presented E material. The study also showed (somewhat expectedly) that when the material they required for the assignment was clear, the student performance did drop. Therefore, it is possible to enhance future delivery of courses through careful reflection and appropriate support. In the end, we must remember innovation is not just restricted to E. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=postgraduate" title="postgraduate">postgraduate</a>, <a href="https://publications.waset.org/abstracts/search?q=engineering" title=" engineering"> engineering</a>, <a href="https://publications.waset.org/abstracts/search?q=assignment" title=" assignment"> assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=perforamance" title=" perforamance"> perforamance</a> </p> <a href="https://publications.waset.org/abstracts/40279/e-learningteaching-and-the-impact-on-student-performance-at-the-postgraduate-level" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40279.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">332</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">191</span> A Practical Guide to Collaborative Writing Assignments as a Pedagogical Technique in Higher Education Implemented in an Economics Course</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Bahia%20Braktia">Bahia Braktia</a>, <a href="https://publications.waset.org/abstracts/search?q=Belkacem%20Braktia"> Belkacem Braktia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Collaborative writing is now an established pedagogical technique in higher education. Since most educators do not have training in the design, execution, and evaluation of writing assignments, implementing such tasks has proven difficult. This paper firstly proposes a framework for a collaborative writing assignment based on a literature study and adopting a writing-to-learn concept. It then describes the research undertaken and shows how this framework is implemented in an economics course, at an Algerian university, with undergraduate students. Finally, using a mixed methods design, it examines the students’ perceptions of what they have learned about collaborative writing. Preliminary results show that group assignments will always be a challenge, but with careful planning and structure, a collaborative writing assignment can be used effectively to help students improve their analytical and critical thinking abilities, research and group work skills, as well as writing proficiency. Students have a positive experience of working in a team and identified a wide variety of different team skills that they have learned through the process. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=collaborative%20writing" title="collaborative writing">collaborative writing</a>, <a href="https://publications.waset.org/abstracts/search?q=research%20assignment" title=" research assignment"> research assignment</a>, <a href="https://publications.waset.org/abstracts/search?q=students%E2%80%99%20perception" title=" students’ perception"> students’ perception</a>, <a href="https://publications.waset.org/abstracts/search?q=survey" title=" survey"> survey</a> </p> <a href="https://publications.waset.org/abstracts/84573/a-practical-guide-to-collaborative-writing-assignments-as-a-pedagogical-technique-in-higher-education-implemented-in-an-economics-course" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/84573.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">203</span> </span> </div> </div> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">190</span> An Evolutionary Multi-Objective Optimization for Airport Gate Assignment Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Seyedmirsajad%20Mokhtarimousavi">Seyedmirsajad Mokhtarimousavi</a>, <a href="https://publications.waset.org/abstracts/search?q=Danial%20Talebi"> Danial Talebi</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamidreza%20Asgari"> Hamidreza Asgari </a> </p> <p class="card-text"><strong>Abstract:</strong></p> Gate Assignment Problem (GAP) is one of the most substantial issues in airport operation. In principle, GAP intends to maintain the maximum capacity of the airport through the best possible allocation of the resources (gates) in order to reach the optimum outcome. The problem involves a wide range of dependent and independent resources and their limitations, which add to the complexity of GAP from both theoretical and practical perspective. In this study, GAP was mathematically formulated as a three-objective problem. The preliminary goal of multi-objective formulation was to address a higher number of objectives that can be simultaneously optimized and therefore increase the practical efficiency of the final solution. The problem is solved by applying the second version of Non-dominated Sorting Genetic Algorithm (NSGA-II). Results showed that the proposed mathematical model could address most of major criteria in the decision-making process in airport management in terms of minimizing both airport/airline cost and passenger walking distance time. Moreover, the proposed approach could properly find acceptable possible answers. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=airport%20management" title="airport management">airport management</a>, <a href="https://publications.waset.org/abstracts/search?q=gate%20assignment%20problem" title=" gate assignment problem"> gate assignment problem</a>, <a href="https://publications.waset.org/abstracts/search?q=mathematical%20modeling" title=" mathematical modeling"> mathematical modeling</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithm" title=" genetic algorithm"> genetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=NSGA-II" title=" NSGA-II"> NSGA-II</a> </p> <a href="https://publications.waset.org/abstracts/63467/an-evolutionary-multi-objective-optimization-for-airport-gate-assignment-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/63467.pdf" target="_blank" class="btn btn-primary btn-sm">PDF</a> <span class="bg-info text-light px-1 py-1 float-right rounded"> Downloads <span class="badge badge-light">299</span> </span> </div> </div> <ul class="pagination"> <li class="page-item disabled"><span class="page-link">&lsaquo;</span></li> <li class="page-item active"><span class="page-link">1</span></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=due-date%20assignment&page=2">2</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=due-date%20assignment&page=3">3</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=due-date%20assignment&page=4">4</a></li> <li class="page-item"><a class="page-link" href="https://publications.waset.org/abstracts/search?q=due-date%20assignment&page=5">5</a></li> <li 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