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scheduling problem</title> <meta name="description" content="Search results for: bus scheduling problem"> <meta name="keywords" content="bus scheduling problem"> <meta name="viewport" content="width=device-width, initial-scale=1, minimum-scale=1, maximum-scale=1, user-scalable=no"> <meta charset="utf-8"> <link href="https://cdn.waset.org/favicon.ico" type="image/x-icon" rel="shortcut icon"> <link href="https://cdn.waset.org/static/plugins/bootstrap-4.2.1/css/bootstrap.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/plugins/fontawesome/css/all.min.css" rel="stylesheet"> <link href="https://cdn.waset.org/static/css/site.css?v=150220211555" rel="stylesheet"> </head> <body> <header> <div class="container"> <nav class="navbar navbar-expand-lg navbar-light"> <a class="navbar-brand" href="https://waset.org"> <img src="https://cdn.waset.org/static/images/wasetc.png" alt="Open Science Research Excellence" title="Open Science Research Excellence" /> </a> <button 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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="bus scheduling problem"> <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> 7414</div> </div> </div> </div> <h1 class="mt-3 mb-3 text-center" style="font-size:1.6rem;">Search results for: bus scheduling problem</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7414</span> A Heuristic Approach for the General Flowshop Scheduling Problem to Minimize the Makespan</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mohsen%20Ziaee">Mohsen Ziaee</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Almost all existing researches on the flowshop scheduling problems focus on the permutation schedules and there is insufficient study dedicated to the general flowshop scheduling problems in the literature, since the modeling and solving of the general flowshop scheduling problems are more difficult than the permutation ones, especially for the large-size problem instances. This paper considers the general flowshop scheduling problem with the objective function of the makespan (F//Cmax). We first find the optimal solution of the problem by solving a mixed integer linear programming model. An efficient heuristic method is then presented to solve the problem. An ant colony optimization algorithm is also proposed for the problem. In order to evaluate the performance of the methods, computational experiments are designed and performed. Numerical results show that the heuristic algorithm can result in reasonable solutions with low computational effort and even achieve optimal solutions in some cases. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=scheduling" title="scheduling">scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=general%20flow%20shop%20scheduling%20problem" title=" general flow shop scheduling problem"> general flow shop scheduling problem</a>, <a href="https://publications.waset.org/abstracts/search?q=makespan" title=" makespan"> makespan</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic" title=" heuristic"> heuristic</a> </p> <a href="https://publications.waset.org/abstracts/92277/a-heuristic-approach-for-the-general-flowshop-scheduling-problem-to-minimize-the-makespan" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/92277.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">7413</span> Metaheuristics to Solve Tasks Scheduling</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Rachid%20Ziteuni">Rachid Ziteuni</a>, <a href="https://publications.waset.org/abstracts/search?q=Selt%20Omar"> Selt Omar</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we propose a new polynomial metaheuristic elaboration (tabu search) for solving scheduling problems. This method allows us to solve the scheduling problem of n tasks on m identical parallel machines with unavailability periods. This problem is NP-complete in the strong sens and finding an optimal solution appears unlikely. Note that all data in this problem are integer and deterministic. The performance criterion to optimize in this problem which we denote Pm/N-c/summs of (wjCj) is the weighted sum of the end dates of tasks. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=scheduling" title="scheduling">scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=parallel%20identical%20machines" title=" parallel identical machines"> parallel identical machines</a>, <a href="https://publications.waset.org/abstracts/search?q=unavailability%20periods" title=" unavailability periods"> unavailability periods</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic" title=" metaheuristic"> metaheuristic</a>, <a href="https://publications.waset.org/abstracts/search?q=tabu%20search" title=" tabu search"> tabu search</a> </p> <a href="https://publications.waset.org/abstracts/5635/metaheuristics-to-solve-tasks-scheduling" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5635.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">330</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">7412</span> A Metaheuristic for the Layout and Scheduling Problem in a Job Shop Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Hern%C3%A1ndez%20Eva%20Selene">Hernández Eva Selene</a>, <a href="https://publications.waset.org/abstracts/search?q=Reyna%20Mary%20Carmen"> Reyna Mary Carmen</a>, <a href="https://publications.waset.org/abstracts/search?q=Rivera%20H%C3%A9ctor"> Rivera Héctor</a>, <a href="https://publications.waset.org/abstracts/search?q=Barrag%C3%A1n%20%20Irving"> Barragán Irving</a> </p> <p class="card-text"><strong>Abstract:</strong></p> We propose an approach that jointly addresses the layout of a facility and the scheduling of a sequence of jobs. In real production, these two problems are interrelated. However, they are treated separately in the literature. Our approach is an extension of the job shop problem with transportation delay, where the location of the machines is selected among possible sites. The model minimizes the makespan, using the short processing times rule with two algorithms; the first one considers all the permutations for the location of machines, and the second only a heuristic to select some specific permutations that reduces computational time. Some instances are proved and compared with literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=layout%20problem" title="layout problem">layout problem</a>, <a href="https://publications.waset.org/abstracts/search?q=job%20shop%20scheduling%20problem" title=" job shop scheduling problem"> job shop scheduling problem</a>, <a href="https://publications.waset.org/abstracts/search?q=concurrent%20scheduling%20and%20layout%20problem" title=" concurrent scheduling and layout problem"> concurrent scheduling and layout problem</a>, <a href="https://publications.waset.org/abstracts/search?q=metaheuristic" title=" metaheuristic"> metaheuristic</a> </p> <a href="https://publications.waset.org/abstracts/31639/a-metaheuristic-for-the-layout-and-scheduling-problem-in-a-job-shop-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/31639.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">606</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">7411</span> Genetic Algorithm for Solving the Flexible Job-Shop Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Guilherme%20Baldo%20Carlos">Guilherme Baldo Carlos</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The flexible job-shop scheduling problem (FJSP) is an NP-hard combinatorial optimization problem, which can be applied to model several applications in a wide array of industries. This problem will have its importance increase due to the shift in the production mode that modern society is going through. The demands are increasing and for products personalized and customized. This work aims to apply a meta-heuristic called a genetic algorithm (GA) to solve this problem. A GA is a meta-heuristic inspired by the natural selection of Charles Darwin; it produces a population of individuals (solutions) and selects, mutates, and mates the individuals through generations in order to find a good solution for the problem. The results found indicate that the GA is suitable for FJSP solving. <p class="card-text"><strong>Keywords:</strong> <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=evolutionary%20algorithm" title=" evolutionary algorithm"> evolutionary algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=flexible%20job-shop%20scheduling" title=" flexible job-shop scheduling"> flexible job-shop scheduling</a> </p> <a href="https://publications.waset.org/abstracts/132314/genetic-algorithm-for-solving-the-flexible-job-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132314.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">7410</span> A Polynomial Approach for a Graphical-based Integrated Production and Transport Scheduling with Capacity Restrictions </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=M.%20Ndeley">M. Ndeley</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The performance of global manufacturing supply chains depends on the interaction of production and transport processes. Currently, the scheduling of these processes is done separately without considering mutual requirements, which leads to no optimal solutions. An integrated scheduling of both processes enables the improvement of supply chain performance. The integrated production and transport scheduling problem (PTSP) is NP-hard, so that heuristic methods are necessary to efficiently solve large problem instances as in the case of global manufacturing supply chains. This paper presents a heuristic scheduling approach which handles the integration of flexible production processes with intermodal transport, incorporating flexible land transport. The method is based on a graph that allows a reformulation of the PTSP as a shortest path problem for each job, which can be solved in polynomial time. The proposed method is applied to a supply chain scenario with a manufacturing facility in South Africa and shipments of finished product to customers within the Country. The obtained results show that the approach is suitable for the scheduling of large-scale problems and can be flexibly adapted to different scenarios. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=production%20and%20transport%20scheduling%20problem" title="production and transport scheduling problem">production and transport scheduling problem</a>, <a href="https://publications.waset.org/abstracts/search?q=graph%20based%20scheduling" title=" graph based scheduling"> graph based scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=integrated%20scheduling" title=" integrated scheduling"> integrated scheduling</a> </p> <a href="https://publications.waset.org/abstracts/30253/a-polynomial-approach-for-a-graphical-based-integrated-production-and-transport-scheduling-with-capacity-restrictions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30253.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">7409</span> Modeling and Simulation of Flow Shop Scheduling Problem through Petri Net Tools</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Joselito%20Medina%20Marin">Joselito Medina Marin</a>, <a href="https://publications.waset.org/abstracts/search?q=Norberto%20Hern%C3%A1ndez%20Romero"> Norberto Hernández Romero</a>, <a href="https://publications.waset.org/abstracts/search?q=Juan%20Carlos%20Seck%20Tuoh%20Mora"> Juan Carlos Seck Tuoh Mora</a>, <a href="https://publications.waset.org/abstracts/search?q=Erick%20S.%20Martinez%20Gomez"> Erick S. Martinez Gomez</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Flow Shop Scheduling Problem (FSSP) is a typical problem that is faced by production planning managers in Flexible Manufacturing Systems (FMS). This problem consists in finding the optimal scheduling to carry out a set of jobs, which are processed in a set of machines or shared resources. Moreover, all the jobs are processed in the same machine sequence. As in all the scheduling problems, the makespan can be obtained by drawing the Gantt chart according to the operations order, among other alternatives. On this way, an FMS presenting the FSSP can be modeled by Petri nets (PNs), which are a powerful tool that has been used to model and analyze discrete event systems. Then, the makespan can be obtained by simulating the PN through the token game animation and incidence matrix. In this work, we present an adaptive PN to obtain the makespan of FSSP by applying PN analytical tools. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flow-shop%20scheduling%20problem" title="flow-shop scheduling problem">flow-shop scheduling problem</a>, <a href="https://publications.waset.org/abstracts/search?q=makespan" title=" makespan"> makespan</a>, <a href="https://publications.waset.org/abstracts/search?q=Petri%20nets" title=" Petri nets"> Petri nets</a>, <a href="https://publications.waset.org/abstracts/search?q=state%20equation" title=" state equation"> state equation</a> </p> <a href="https://publications.waset.org/abstracts/48746/modeling-and-simulation-of-flow-shop-scheduling-problem-through-petri-net-tools" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48746.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">298</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">7408</span> Multi-Objective Multi-Mode Resource-Constrained Project Scheduling Problem by Preemptive Fuzzy Goal Programming</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Busaba%20Phurksaphanrat">Busaba Phurksaphanrat</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research proposes a pre-emptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of make-span. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, pre-emptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=multi-mode%20resource%20constrained%20project%20scheduling%20problem" title="multi-mode resource constrained project scheduling problem">multi-mode resource constrained project scheduling problem</a>, <a href="https://publications.waset.org/abstracts/search?q=fuzzy%20set" title=" fuzzy set"> fuzzy set</a>, <a href="https://publications.waset.org/abstracts/search?q=goal%20programming" title=" goal programming"> goal programming</a>, <a href="https://publications.waset.org/abstracts/search?q=pre-emptive%20fuzzy%20goal%20programming" title=" pre-emptive fuzzy goal programming"> pre-emptive fuzzy goal programming</a> </p> <a href="https://publications.waset.org/abstracts/5799/multi-objective-multi-mode-resource-constrained-project-scheduling-problem-by-preemptive-fuzzy-goal-programming" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/5799.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">435</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">7407</span> Trends in Solving Assembly Job Shop Scheduling Problem: A Review</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Midhun%20Paul">Midhun Paul</a>, <a href="https://publications.waset.org/abstracts/search?q=T.%20Radha%20Ramanan"> T. Radha Ramanan</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The objective of this work is to present a state-of-the-art literature review highlighting the challenges in the research of the scheduling of assembly job shop problem and providing an insight on how the future directions of the research would be. The number of work has been substantial that it requires a review to enable one to understand the origin of the research and how it is getting evolved. This review paper presents a comprehensive review of the literature dealing with various studies carried on assembly job shop scheduling. The review details the evolution of the AJS from the perspective of other scheduling problems and also presents a classification scheme. The work also identifies the potential directions for future research, which we believe to be worthwhile considering. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=assembly%20job%20shop" title="assembly job shop">assembly job shop</a>, <a href="https://publications.waset.org/abstracts/search?q=future%20directions" title=" future directions"> future directions</a>, <a href="https://publications.waset.org/abstracts/search?q=manufacturing" title=" manufacturing"> manufacturing</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a> </p> <a href="https://publications.waset.org/abstracts/2449/trends-in-solving-assembly-job-shop-scheduling-problem-a-review" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/2449.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">412</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">7406</span> Tabu Search Algorithm for Ship Routing and Scheduling Problem with Time Window</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Khaled%20Moh.%20Alhamad">Khaled Moh. Alhamad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper describes a tabu search heuristic for a ship routing and scheduling problem (SRSP). The method was developed to address the problem of loading cargos for many customers using heterogeneous vessels. Constraints relate to delivery time windows imposed by customers, the time horizon by which all deliveries must be made and vessel capacities. The results of a computational investigation are presented. Solution quality and execution time are explored with respect to problem size and parameters controlling the tabu search such as tenure and neighbourhood size. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heuristic" title="heuristic">heuristic</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</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=transportation" title=" transportation"> transportation</a> </p> <a href="https://publications.waset.org/abstracts/43484/tabu-search-algorithm-for-ship-routing-and-scheduling-problem-with-time-window" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/43484.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">506</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">7405</span> A Reactive Flexible Job Shop Scheduling Model in a Stochastic Environment</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Majid%20Khalili">Majid Khalili</a>, <a href="https://publications.waset.org/abstracts/search?q=Hamed%20Tayebi"> Hamed Tayebi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper considers a stochastic flexible job-shop scheduling (SFJSS) problem in the presence of production disruptions, and reactive scheduling is implemented in order to find the optimal solution under uncertainty. In this problem, there are two main disruptions including machine failure which influences operation time, and modification or cancellation of the order delivery date during production. In order to decrease the negative effects of these difficulties, two derived strategies from reactive scheduling are used; the first one is relevant to being able to allocate multiple machine to each job, and the other one is related to being able to select the best alternative process from other job while some disruptions would be created in the processes of a job. For this purpose, a Mixed Integer Linear Programming model is proposed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=flexible%20job-shop%20scheduling" title="flexible job-shop scheduling">flexible job-shop scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=reactive%20scheduling" title=" reactive scheduling"> reactive scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=stochastic%20environment" title=" stochastic environment"> stochastic environment</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed%20integer%20linear%20programming" title=" mixed integer linear programming"> mixed integer linear programming</a> </p> <a href="https://publications.waset.org/abstracts/69932/a-reactive-flexible-job-shop-scheduling-model-in-a-stochastic-environment" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69932.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">360</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">7404</span> Presenting a Job Scheduling Algorithm Based on Learning Automata in Computational Grid</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Roshanak%20Khodabakhsh%20Jolfaei">Roshanak Khodabakhsh Jolfaei</a>, <a href="https://publications.waset.org/abstracts/search?q=Javad%20Akbari%20Torkestani"> Javad Akbari Torkestani</a> </p> <p class="card-text"><strong>Abstract:</strong></p> As a cooperative environment for problem-solving, it is necessary that grids develop efficient job scheduling patterns with regard to their goals, domains and structure. Since the Grid environments facilitate distributed calculations, job scheduling appears in the form of a critical problem for the management of Grid sources that influences severely on the efficiency for the whole Grid environment. Due to the existence of some specifications such as sources dynamicity and conditions of the network in Grid, some algorithm should be presented to be adjustable and scalable with increasing the network growth. For this purpose, in this paper a job scheduling algorithm has been presented on the basis of learning automata in computational Grid which the performance of its results were compared with FPSO algorithm (Fuzzy Particle Swarm Optimization algorithm) and GJS algorithm (Grid Job Scheduling algorithm). The obtained numerical results indicated the superiority of suggested algorithm in comparison with FPSO and GJS. In addition, the obtained results classified FPSO and GJS in the second and third position respectively after the mentioned algorithm. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=computational%20grid" title="computational grid">computational grid</a>, <a href="https://publications.waset.org/abstracts/search?q=job%20scheduling" title=" job scheduling"> job scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=learning%20automata" title=" learning automata"> learning automata</a>, <a href="https://publications.waset.org/abstracts/search?q=dynamic%20scheduling" title=" dynamic scheduling"> dynamic scheduling</a> </p> <a href="https://publications.waset.org/abstracts/40508/presenting-a-job-scheduling-algorithm-based-on-learning-automata-in-computational-grid" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40508.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">343</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">7403</span> Integer Programming: Domain Transformation in Nurse Scheduling Problem.</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Geetha%20Baskaran">Geetha Baskaran</a>, <a href="https://publications.waset.org/abstracts/search?q=Andrzej%20Barjiela"> Andrzej Barjiela</a>, <a href="https://publications.waset.org/abstracts/search?q=Rong%20Qu"> Rong Qu</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Motivation: Nurse scheduling is a complex combinatorial optimization problem. It is also known as NP-hard. It needs an efficient re-scheduling to minimize some trade-off of the measures of violation by reducing selected constraints to soft constraints with measurements of their violations. Problem Statement: In this paper, we extend our novel approach to solve the nurse scheduling problem by transforming it through Information Granulation. Approach: This approach satisfies the rules of a typical hospital environment based on a standard benchmark problem. Generating good work schedules has a great influence on nurses' working conditions which are strongly related to the level of a quality health care. Domain transformation that combines the strengths of operation research and artificial intelligence was proposed for the solution of the problem. Compared to conventional methods, our approach involves judicious grouping (information granulation) of shifts types’ that transforms the original problem into a smaller solution domain. Later these schedules from the smaller problem domain are converted back into the original problem domain by taking into account the constraints that could not be represented in the smaller domain. An Integer Programming (IP) package is used to solve the transformed scheduling problem by expending the branch and bound algorithm. We have used the GNU Octave for Windows to solve this problem. Results: The scheduling problem has been solved in the proposed formalism resulting in a high quality schedule. Conclusion: Domain transformation represents departure from a conventional one-shift-at-a-time scheduling approach. It offers an advantage of efficient and easily understandable solutions as well as offering deterministic reproducibility of the results. We note, however, that it does not guarantee the global optimum. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=domain%20transformation" title="domain transformation">domain transformation</a>, <a href="https://publications.waset.org/abstracts/search?q=nurse%20scheduling" title=" nurse scheduling"> nurse scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=information%20granulation" title=" information granulation"> information granulation</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation "> simulation </a> </p> <a href="https://publications.waset.org/abstracts/1492/integer-programming-domain-transformation-in-nurse-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/1492.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">397</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">7402</span> Resource-Constrained Heterogeneous Workflow Scheduling Algorithms in Heterogeneous Computing Clusters</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Lei%20Wang">Lei Wang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiahao%20Zhou"> Jiahao Zhou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The development of heterogeneous computing clusters provides a strong computility guarantee for large-scale workflows (e.g., scientific computing, artificial intelligence (AI), etc.). However, the tasks within large-scale workflows have also gradually become heterogeneous due to different demands on computing resources, which leads to the addition of a task resource-restricted constraint to the workflow scheduling problem on heterogeneous computing platforms. In this paper, we propose a heterogeneous constrained minimum makespan scheduling algorithm based on the idea of greedy strategy, which provides an efficient solution to the heterogeneous workflow scheduling problem in a heterogeneous platform. In this paper, we test the effectiveness of our proposed scheduling algorithm by randomly generating heterogeneous workflows with heterogeneous computing platform, and the experiments show that our method improves 15.2% over the state-of-the-art methods. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=heterogeneous%20computing" title="heterogeneous computing">heterogeneous computing</a>, <a href="https://publications.waset.org/abstracts/search?q=workflow%20scheduling" title=" workflow scheduling"> workflow scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=constrained%20resources" title=" constrained resources"> constrained resources</a>, <a href="https://publications.waset.org/abstracts/search?q=minimal%20makespan" title=" minimal makespan"> minimal makespan</a> </p> <a href="https://publications.waset.org/abstracts/190199/resource-constrained-heterogeneous-workflow-scheduling-algorithms-in-heterogeneous-computing-clusters" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/190199.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">33</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">7401</span> A Combined Meta-Heuristic with Hyper-Heuristic Approach to Single Machine Production Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=C.%20E.%20Nugraheni">C. E. Nugraheni</a>, <a href="https://publications.waset.org/abstracts/search?q=L.%20Abednego"> L. Abednego</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper is concerned with minimization of mean tardiness and flow time in a real single machine production scheduling problem. Two variants of genetic algorithm as meta-heuristic are combined with hyper-heuristic approach are proposed to solve this problem. These methods are used to solve instances generated with real world data from a company. Encouraging results are reported. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hyper-heuristics" title="hyper-heuristics">hyper-heuristics</a>, <a href="https://publications.waset.org/abstracts/search?q=evolutionary%20algorithms" title=" evolutionary algorithms"> evolutionary algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=production%20scheduling" title=" production scheduling"> production scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=meta-heuristic" title=" meta-heuristic"> meta-heuristic</a> </p> <a href="https://publications.waset.org/abstracts/12732/a-combined-meta-heuristic-with-hyper-heuristic-approach-to-single-machine-production-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/12732.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">381</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">7400</span> Performance Evaluation of Task Scheduling Algorithm on LCQ Network</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zaki%20Ahmad%20Khan">Zaki Ahmad Khan</a>, <a href="https://publications.waset.org/abstracts/search?q=Jamshed%20Siddiqui"> Jamshed Siddiqui</a>, <a href="https://publications.waset.org/abstracts/search?q=Abdus%20Samad"> Abdus Samad</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Scheduling and mapping of tasks on a set of processors is considered as a critical problem in parallel and distributed computing system. This paper deals with the problem of dynamic scheduling on a special type of multiprocessor architecture known as Linear Crossed Cube (LCQ) network. This proposed multiprocessor is a hybrid network which combines the features of both linear type of architectures as well as cube based architectures. Two standard dynamic scheduling schemes namely Minimum Distance Scheduling (MDS) and Two Round Scheduling (TRS) schemes are implemented on the LCQ network. Parallel tasks are mapped and the imbalance of load is evaluated on different set of processors in LCQ network. The simulations results are evaluated and effort is made by means of through analysis of the results to obtain the best solution for the given network in term of load imbalance left and execution time. The other performance matrices like speedup and efficiency are also evaluated with the given dynamic algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=dynamic%20algorithm" title="dynamic algorithm">dynamic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=load%20imbalance" title=" load imbalance"> load imbalance</a>, <a href="https://publications.waset.org/abstracts/search?q=mapping" title=" mapping"> mapping</a>, <a href="https://publications.waset.org/abstracts/search?q=task%20scheduling" title=" task scheduling"> task scheduling</a> </p> <a href="https://publications.waset.org/abstracts/20290/performance-evaluation-of-task-scheduling-algorithm-on-lcq-network" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/20290.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">449</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">7399</span> Job Shop Scheduling: Classification, Constraints and Objective Functions</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Majid%20Abdolrazzagh-Nezhad">Majid Abdolrazzagh-Nezhad</a>, <a href="https://publications.waset.org/abstracts/search?q=Salwani%20Abdullah"> Salwani Abdullah</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The job-shop scheduling problem (JSSP) is an important decision facing those involved in the fields of industry, economics and management. This problem is a class of combinational optimization problem known as the NP-hard problem. JSSPs deal with a set of machines and a set of jobs with various predetermined routes through the machines, where the objective is to assemble a schedule of jobs that minimizes certain criteria such as makespan, maximum lateness, and total weighted tardiness. Over the past several decades, interest in meta-heuristic approaches to address JSSPs has increased due to the ability of these approaches to generate solutions which are better than those generated from heuristics alone. This article provides the classification, constraints and objective functions imposed on JSSPs that are available in the literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=job-shop%20scheduling" title="job-shop scheduling">job-shop scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=classification" title=" classification"> classification</a>, <a href="https://publications.waset.org/abstracts/search?q=constraints" title=" constraints"> constraints</a>, <a href="https://publications.waset.org/abstracts/search?q=objective%20functions" title=" objective functions"> objective functions</a> </p> <a href="https://publications.waset.org/abstracts/58284/job-shop-scheduling-classification-constraints-and-objective-functions" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58284.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">444</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">7398</span> A Heuristic for the Integrated Production and Distribution Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Christian%20Meinecke">Christian Meinecke</a>, <a href="https://publications.waset.org/abstracts/search?q=Bernd%20Scholz-Reiter"> Bernd Scholz-Reiter</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The integrated problem of production and distribution scheduling is relevant in many industrial applications. Thus, many heuristics to solve this integrated problem have been developed in the last decade. Most of these heuristics use a sequential working principal or a single decomposition and integration approach to separate and solve sub-problems. A heuristic using a multi-step decomposition and integration approach is presented in this paper and evaluated in a case study. The result show significant improved results compared with sequential scheduling heuristics. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=production%20and%20outbound%20distribution" title="production and outbound distribution">production and outbound distribution</a>, <a href="https://publications.waset.org/abstracts/search?q=integrated%20planning" title=" integrated planning"> integrated planning</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic" title=" heuristic"> heuristic</a>, <a href="https://publications.waset.org/abstracts/search?q=decomposition" title=" decomposition"> decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=integration" title=" integration"> integration</a> </p> <a href="https://publications.waset.org/abstracts/4364/a-heuristic-for-the-integrated-production-and-distribution-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/4364.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">429</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">7397</span> Timetabling Communities’ Demands for an Effective Examination Timetabling Using Integer Linear Programming</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=N.%20F.%20Jamaluddin">N. F. Jamaluddin</a>, <a href="https://publications.waset.org/abstracts/search?q=N.%20A.%20H.%20Aizam"> N. A. H. Aizam</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper explains the educational timetabling problem, a type of scheduling problem that is considered as one of the most challenging problem in optimization and operational research. The university examination timetabling problem (UETP), which involves assigning a set number of exams into a set number of timeslots whilst fulfilling all required conditions, has been widely investigated. The limitation of available timeslots and resources with the increasing number of examinations are the main reasons in the difficulty of solving this problem. Dynamical change in the examination scheduling system adds up the complication particularly in coping up with the demand and new requirements by the communities. Our objective is to investigate these demands and requirements with subjects taken from Universiti Malaysia Terengganu (UMT), through questionnaires. Integer linear programming model which reflects the preferences obtained to produce an effective examination timetabling was formed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=demands" title="demands">demands</a>, <a href="https://publications.waset.org/abstracts/search?q=educational%20timetabling" title=" educational timetabling"> educational timetabling</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=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=university%20examination%20timetabling%20problem%20%28UETP%29" title=" university examination timetabling problem (UETP)"> university examination timetabling problem (UETP)</a> </p> <a href="https://publications.waset.org/abstracts/49545/timetabling-communities-demands-for-an-effective-examination-timetabling-using-integer-linear-programming" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/49545.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">337</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">7396</span> Pre- and Post-Analyses of Disruptive Quay Crane Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=K.%20-H.%20Yang">K. -H. Yang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In the past, the quay crane operations have been well studied. There were a certain number of scheduling algorithms for quay crane operations, but without considering some nuisance factors that might disrupt the quay crane operations. For example, bad grapples make a crane unable to load or unload containers or a sudden strong breeze stops operations temporarily. Although these disruptive conditions randomly occur, they influence the efficiency of quay crane operations. The disruption is not considered in the operational procedures nor is evaluated in advance for its impacts. This study applies simulation and optimization approaches to develop structures of pre-analysis and post-analysis for the Quay Crane Scheduling Problem to deal with disruptive scenarios for quay crane operation. Numerical experiments are used for demonstrations for the validity of the developed approaches. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=disruptive%20quay%20crane%20scheduling" title="disruptive quay crane scheduling">disruptive quay crane scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=pre-analysis" title=" pre-analysis"> pre-analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=post-analysis" title=" post-analysis"> post-analysis</a>, <a href="https://publications.waset.org/abstracts/search?q=disruption" title=" disruption"> disruption</a> </p> <a href="https://publications.waset.org/abstracts/88036/pre-and-post-analyses-of-disruptive-quay-crane-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/88036.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">222</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">7395</span> A Bi-Objective Model to Address Simultaneous Formulation of Project Scheduling and Material Ordering</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Babak%20H.%20Tabrizi">Babak H. Tabrizi</a>, <a href="https://publications.waset.org/abstracts/search?q=Seyed%20Farid%20Ghaderi"> Seyed Farid Ghaderi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Concurrent planning of project scheduling and material ordering has been increasingly addressed within last decades as an approach to improve the project execution costs. Therefore, we have taken the problem into consideration in this paper, aiming to maximize schedules quality robustness, in addition to minimize the relevant costs. In this regard, a bi-objective mathematical model is developed to formulate the problem. Moreover, it is possible to utilize the all-unit discount for materials purchasing. The problem is then solved by the constraint method, and the Pareto front is obtained for a variety of robustness values. The applicability and efficiency of the proposed model is tested by different numerical instances, finally. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=e-constraint%20method" title="e-constraint method">e-constraint method</a>, <a href="https://publications.waset.org/abstracts/search?q=material%20ordering" title=" material ordering"> material ordering</a>, <a href="https://publications.waset.org/abstracts/search?q=project%20management" title=" project management"> project management</a>, <a href="https://publications.waset.org/abstracts/search?q=project%20scheduling" title=" project scheduling"> project scheduling</a> </p> <a href="https://publications.waset.org/abstracts/40333/a-bi-objective-model-to-address-simultaneous-formulation-of-project-scheduling-and-material-ordering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40333.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">295</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">7394</span> Benders Decomposition Approach to Solve the Hybrid Flow Shop Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ebrahim%20Asadi-Gangraj">Ebrahim Asadi-Gangraj</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Hybrid flow shop scheduling problem (HFS) contains sequencing in a flow shop where, at any stage, there exist one or more related or unrelated parallel machines. This production system is a common manufacturing environment in many real industries, such as the steel manufacturing, ceramic tile manufacturing, and car assembly industries. In this research, a mixed integer linear programming (MILP) model is presented for the hybrid flow shop scheduling problem, in which, the objective consists of minimizing the maximum completion time (makespan). For this purpose, a Benders Decomposition (BD) method is developed to solve the research problem. The proposed approach is tested on some test problems, small to moderate scale. The experimental results show that the Benders decomposition approach can solve the hybrid flow shop scheduling problem in a reasonable time, especially for small and moderate-size test problems. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=hybrid%20flow%20shop" title="hybrid flow shop">hybrid flow shop</a>, <a href="https://publications.waset.org/abstracts/search?q=mixed%20integer%20linear%20programming" title=" mixed integer linear programming"> mixed integer linear programming</a>, <a href="https://publications.waset.org/abstracts/search?q=Benders%20decomposition" title=" Benders decomposition"> Benders decomposition</a>, <a href="https://publications.waset.org/abstracts/search?q=makespan" title=" makespan"> makespan</a> </p> <a href="https://publications.waset.org/abstracts/106041/benders-decomposition-approach-to-solve-the-hybrid-flow-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/106041.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">188</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">7393</span> A Hybrid Distributed Algorithm for Solving Job Shop Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Aydin%20Teymourifar">Aydin Teymourifar</a>, <a href="https://publications.waset.org/abstracts/search?q=Gurkan%20Ozturk"> Gurkan Ozturk</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, a distributed hybrid algorithm is proposed for solving the job shop scheduling problem. The suggested method executes different artificial neural networks, heuristics and meta-heuristics simultaneously on more than one machine. The neural networks are used to control the constraints of the problem while the meta-heuristics search the global space and the heuristics are used to prevent the premature convergence. To attain an efficient distributed intelligent method for solving big and distributed job shop scheduling problems, Apache Spark and Hadoop frameworks are used. In the algorithm implementation and design steps, new approaches are applied. Comparison between the proposed algorithm and other efficient algorithms from the literature shows its efficiency, which is able to solve large size problems in short time. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=distributed%20algorithms" title="distributed algorithms">distributed algorithms</a>, <a href="https://publications.waset.org/abstracts/search?q=Apache%20Spark" title=" Apache Spark"> Apache Spark</a>, <a href="https://publications.waset.org/abstracts/search?q=Hadoop" title=" Hadoop"> Hadoop</a>, <a href="https://publications.waset.org/abstracts/search?q=job%20shop%20scheduling" title=" job shop scheduling"> job shop scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=neural%20network" title=" neural network"> neural network</a> </p> <a href="https://publications.waset.org/abstracts/72320/a-hybrid-distributed-algorithm-for-solving-job-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/72320.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">387</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">7392</span> Models, Resources and Activities of Project Scheduling Problems</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Jorge%20A.%20Ruiz-Vanoye">Jorge A. Ruiz-Vanoye</a>, <a href="https://publications.waset.org/abstracts/search?q=Ocotl%C3%A1n%20D%C3%ADaz-Parra"> Ocotlán Díaz-Parra</a>, <a href="https://publications.waset.org/abstracts/search?q=Alejandro%20Fuentes-Penna"> Alejandro Fuentes-Penna</a>, <a href="https://publications.waset.org/abstracts/search?q=Jos%C3%A9%20J.%20Hern%C3%A1ndez-Flores"> José J. Hernández-Flores</a>, <a href="https://publications.waset.org/abstracts/search?q=Edith%20Olaco%20Garcia"> Edith Olaco Garcia</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Project Scheduling Problem (PSP) is a generic name given to a whole class of problems in which the best form, time, resources and costs for project scheduling are necessary. The PSP is an application area related to the project management. This paper aims at being a guide to understand PSP by presenting a survey of the general parameters of PSP: the Resources (those elements that realize the activities of a project), and the Activities (set of operations or own tasks of a person or organization); the mathematical models of the main variants of PSP and the algorithms used to solve the variants of the PSP. The project scheduling is an important task in project management. This paper contains mathematical models, resources, activities, and algorithms of project scheduling problems. The project scheduling problem has attracted researchers of the automotive industry, steel manufacturer, medical research, pharmaceutical research, telecommunication, industry, aviation industry, development of the software, manufacturing management, innovation and technology management, construction industry, government project management, financial services, machine scheduling, transportation management, and others. The project managers need to finish a project with the minimum cost and the maximum quality. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=PSP" title="PSP">PSP</a>, <a href="https://publications.waset.org/abstracts/search?q=Combinatorial%20Optimization%20Problems" title=" Combinatorial Optimization Problems"> Combinatorial Optimization Problems</a>, <a href="https://publications.waset.org/abstracts/search?q=Project%20Management%3B%20Manufacturing%20Management" title=" Project Management; Manufacturing Management"> Project Management; Manufacturing Management</a>, <a href="https://publications.waset.org/abstracts/search?q=Technology%20Management." title=" Technology Management."> Technology Management.</a> </p> <a href="https://publications.waset.org/abstracts/42789/models-resources-and-activities-of-project-scheduling-problems" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/42789.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">418</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">7391</span> Discrete Breeding Swarm for Cost Minimization of Parallel Job Shop Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Tarek%20Aboueldahab">Tarek Aboueldahab</a>, <a href="https://publications.waset.org/abstracts/search?q=Hanan%20Farag"> Hanan Farag</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Parallel Job Shop Scheduling Problem (JSP) is a multi-objective and multi constrains NP- optimization problem. Traditional Artificial Intelligence techniques have been widely used; however, they could be trapped into the local minimum without reaching the optimum solution, so we propose a hybrid Artificial Intelligence model (AI) with Discrete Breeding Swarm (DBS) added to traditional Artificial Intelligence to avoid this trapping. This model is applied in the cost minimization of the Car Sequencing and Operator Allocation (CSOA) problem. The practical experiment shows that our model outperforms other techniques in cost minimization. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=parallel%20job%20shop%20scheduling%20problem" title="parallel job shop scheduling problem">parallel job shop scheduling problem</a>, <a href="https://publications.waset.org/abstracts/search?q=artificial%20intelligence" title=" artificial intelligence"> artificial intelligence</a>, <a href="https://publications.waset.org/abstracts/search?q=discrete%20breeding%20swarm" title=" discrete breeding swarm"> discrete breeding swarm</a>, <a href="https://publications.waset.org/abstracts/search?q=car%20sequencing%20and%20operator%20allocation" title=" car sequencing and operator allocation"> car sequencing and operator allocation</a>, <a href="https://publications.waset.org/abstracts/search?q=cost%20minimization" title=" cost minimization"> cost minimization</a> </p> <a href="https://publications.waset.org/abstracts/132701/discrete-breeding-swarm-for-cost-minimization-of-parallel-job-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/132701.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">187</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">7390</span> M-Machine Assembly Scheduling Problem to Minimize Total Tardiness with Non-Zero Setup Times</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Harun%20Aydilek">Harun Aydilek</a>, <a href="https://publications.waset.org/abstracts/search?q=Asiye%20Aydilek"> Asiye Aydilek</a>, <a href="https://publications.waset.org/abstracts/search?q=Ali%20Allahverdi"> Ali Allahverdi</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Our objective is to minimize the total tardiness in an m-machine two-stage assembly flowshop scheduling problem. The objective is an important performance measure because of the fact that the fulfillment of due dates of customers has to be taken into account while making scheduling decisions. In the literature, the problem is considered with zero setup times which may not be realistic and appropriate for some scheduling environments. Considering separate setup times from processing times increases machine utilization by decreasing the idle time and reduces total tardiness. We propose two new algorithms and adapt four existing algorithms in the literature which are different versions of simulated annealing and genetic algorithms. Moreover, a dominance relation is developed based on the mathematical formulation of the problem. The developed dominance relation is incorporated in our proposed algorithms. Computational experiments are conducted to investigate the performance of the newly proposed algorithms. We find that one of the proposed algorithms performs significantly better than the others, i.e., the error of the best algorithm is less than those of the other algorithms by minimum 50%. The newly proposed algorithm is also efficient for the case of zero setup times and performs better than the best existing algorithm in the literature. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=algorithm" title="algorithm">algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=assembly%20flowshop" title=" assembly flowshop"> assembly flowshop</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=total%20tardiness" title=" total tardiness"> total tardiness</a> </p> <a href="https://publications.waset.org/abstracts/47645/m-machine-assembly-scheduling-problem-to-minimize-total-tardiness-with-non-zero-setup-times" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/47645.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">329</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">7389</span> Single Machine Scheduling Problem to Minimize the Number of Tardy Jobs</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ali%20Allahverdi">Ali Allahverdi</a>, <a href="https://publications.waset.org/abstracts/search?q=Harun%20Aydilek"> Harun Aydilek</a>, <a href="https://publications.waset.org/abstracts/search?q=Asiye%20Aydilek"> Asiye Aydilek</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Minimizing the number of tardy jobs is an important factor to consider while making scheduling decisions. This is because on-time shipments are vital for lowering cost and increasing customers’ satisfaction. This paper addresses the single machine scheduling problem with the objective of minimizing the number of tardy jobs. The only known information is the lower and upper bounds for processing times, and deterministic job due dates. A dominance relation is established, and an algorithm is proposed. Several heuristics are generated from the proposed algorithm. Computational analysis indicates that the performance of one of the heuristics is very close to the optimal solution, i.e., on average, less than 1.5 % from the optimal solution. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=single%20machine%20scheduling" title="single machine scheduling">single machine scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=number%20of%20tardy%20jobs" title=" number of tardy jobs"> number of tardy jobs</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristi" title=" heuristi"> heuristi</a>, <a href="https://publications.waset.org/abstracts/search?q=lower%20and%20upper%20bounds" title=" lower and upper bounds"> lower and upper bounds</a> </p> <a href="https://publications.waset.org/abstracts/21639/single-machine-scheduling-problem-to-minimize-the-number-of-tardy-jobs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/21639.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">555</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">7388</span> Heuristic for Scheduling Correlated Parallel Machine to Minimize Maximum Lateness and Total Weighed Completion Time</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yang-Kuei%20Lin">Yang-Kuei Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Yun-Xi%20Zhang"> Yun-Xi Zhang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This research focuses on the bicriteria correlated parallel machine scheduling problem. The two objective functions considered in this problem are to minimize maximum lateness and total weighted completion time. We first present a mixed integer programming (MIP) model that can find the entire efficient frontier for the studied problem. Next, we have proposed a bicriteria heuristic that can find non-dominated solutions for the studied problem. The performance of the proposed bicriteria heuristic is compared with the efficient frontier generated by solving the MIP model. Computational results indicate that the proposed bicriteria heuristic can solve the problem efficiently and find a set of diverse solutions that are uniformly distributed along the efficient frontier. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=bicriteria" title="bicriteria">bicriteria</a>, <a href="https://publications.waset.org/abstracts/search?q=correlated%20parallel%20machines" title=" correlated parallel machines"> correlated parallel machines</a>, <a href="https://publications.waset.org/abstracts/search?q=heuristic" title=" heuristic"> heuristic</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a> </p> <a href="https://publications.waset.org/abstracts/108546/heuristic-for-scheduling-correlated-parallel-machine-to-minimize-maximum-lateness-and-total-weighed-completion-time" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/108546.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">141</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">7387</span> Solving Operating Room Scheduling Problem by Using Dispatching Rule</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yang-Kuei%20Lin">Yang-Kuei Lin</a>, <a href="https://publications.waset.org/abstracts/search?q=Yin-Yi%20Chou"> Yin-Yi Chou</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this research, we have considered operating room scheduling problem. The objective is to minimize total operating cost. The total operating cost includes idle cost and overtime cost. We have proposed a dispatching rule that can guarantee to find feasible solutions for the studied problem efficiently. We compared the proposed dispatching rule with the optimal solutions found by solving Inter Programming, and other solutions found by using modified existing dispatching rules. The computational results indicates that the proposed heuristic can find near optimal solutions efficiently. <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=dispatching%20rule" title=" dispatching rule"> dispatching rule</a>, <a href="https://publications.waset.org/abstracts/search?q=operation%20rooms" title=" operation rooms"> operation rooms</a>, <a href="https://publications.waset.org/abstracts/search?q=scheduling" title=" scheduling"> scheduling</a> </p> <a href="https://publications.waset.org/abstracts/91669/solving-operating-room-scheduling-problem-by-using-dispatching-rule" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/91669.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">233</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">7386</span> The Utilization of Particle Swarm Optimization Method to Solve Nurse Scheduling Problem </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Norhayati%20Mohd%20Rasip">Norhayati Mohd Rasip</a>, <a href="https://publications.waset.org/abstracts/search?q=Abd.%20Samad%20Hasan%20Basari"> Abd. Samad Hasan Basari </a>, <a href="https://publications.waset.org/abstracts/search?q=Nuzulha%20Khilwani%20Ibrahim"> Nuzulha Khilwani Ibrahim</a>, <a href="https://publications.waset.org/abstracts/search?q=Burairah%20Hussin"> Burairah Hussin</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The allocation of working schedule especially for shift environment is hard to fulfill its fairness among them. In the case of nurse scheduling, to set up the working time table for them is time consuming and complicated, which consider many factors including rules, regulation and human factor. The scenario is more complicated since most nurses are women which have personnel constraints and maternity leave factors. The undesirable schedule can affect the nurse productivity, social life and the absenteeism can significantly as well affect patient's life. This paper aimed to enhance the scheduling process by utilizing the particle swarm optimization in order to solve nurse scheduling problem. The result shows that the generated multiple initial schedule is fulfilled the requirements and produces the lowest cost of constraint violation. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=nurse%20scheduling" title="nurse scheduling">nurse scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=particle%20swarm%20optimisation" title=" particle swarm optimisation"> particle swarm optimisation</a>, <a href="https://publications.waset.org/abstracts/search?q=nurse%20rostering" title=" nurse rostering"> nurse rostering</a>, <a href="https://publications.waset.org/abstracts/search?q=hard%20and%20soft%20constraint" title=" hard and soft constraint"> hard and soft constraint</a> </p> <a href="https://publications.waset.org/abstracts/30425/the-utilization-of-particle-swarm-optimization-method-to-solve-nurse-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/30425.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">372</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">7385</span> A Memetic Algorithm for an Energy-Costs-Aware Flexible Job-Shop Scheduling Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Christian%20B%C3%B6ning">Christian Böning</a>, <a href="https://publications.waset.org/abstracts/search?q=Henrik%20Prinzhorn"> Henrik Prinzhorn</a>, <a href="https://publications.waset.org/abstracts/search?q=Eric%20C.%20Hund"> Eric C. Hund</a>, <a href="https://publications.waset.org/abstracts/search?q=Malte%20Stonis"> Malte Stonis</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this article, the flexible job-shop scheduling problem is extended by consideration of energy costs which arise owing to the power peak, and further decision variables such as work in process and throughput time are incorporated into the objective function. This enables a production plan to be simultaneously optimized in respect of the real arising energy and logistics costs. The energy-costs-aware flexible job-shop scheduling problem (EFJSP) which arises is described mathematically, and a memetic algorithm (MA) is presented as a solution. In the MA, the evolutionary process is supplemented with a local search. Furthermore, repair procedures are used in order to rectify any infeasible solutions that have arisen in the evolutionary process. The potential for lowering the real arising costs of a production plan through consideration of energy consumption levels is highlighted. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=energy%20costs" title="energy costs">energy costs</a>, <a href="https://publications.waset.org/abstracts/search?q=flexible%20job-shop%20scheduling" title=" flexible job-shop scheduling"> flexible job-shop scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=memetic%20algorithm" title=" memetic algorithm"> memetic algorithm</a>, <a href="https://publications.waset.org/abstracts/search?q=power%20peak" title=" power peak"> power peak</a> </p> <a href="https://publications.waset.org/abstracts/69892/a-memetic-algorithm-for-an-energy-costs-aware-flexible-job-shop-scheduling-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/69892.pdf" target="_blank" class="btn btn-primary 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