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results for: concurrent scheduling and layout problem</h1> <div class="card paper-listing mb-3 mt-3"> <h5 class="card-header" style="font-size:.9rem"><span class="badge badge-info">7895</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">7894</span> Optimization of Scheduling through Altering Layout Using Pro-Model </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Zouhair%20Issa%20Ahmed">Zouhair Issa Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Abdulrasool%20Ahmed"> Ahmed Abdulrasool Ahmed</a>, <a href="https://publications.waset.org/abstracts/search?q=Falah%20Hassan%20Abdulsada"> Falah Hassan Abdulsada</a> </p> <p class="card-text"><strong>Abstract:</strong></p> This paper presents a layout of a factory using Pro-Model simulation by choosing the best layout that gives the highest productivity and least work in process. The general problem is to find the best sequence in which jobs pass between the machines which are compatible with the technological constraints and optimal with respect to some performance criteria. The best simulation with Pro-Model program increased productivity and reduced work in process by balancing lines of production compared with the current layout of factory when productivity increased from 45 products to 180 products through 720 hours. <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=Pro-Model" title=" Pro-Model"> Pro-Model</a>, <a href="https://publications.waset.org/abstracts/search?q=simulation" title=" simulation"> simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=balancing%20lines%20of%20production" title=" balancing lines of production"> balancing lines of production</a>, <a href="https://publications.waset.org/abstracts/search?q=layout%20planning" title=" layout planning"> layout planning</a>, <a href="https://publications.waset.org/abstracts/search?q=WIP" title=" WIP "> WIP </a> </p> <a href="https://publications.waset.org/abstracts/8498/optimization-of-scheduling-through-altering-layout-using-pro-model" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/8498.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">636</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">7893</span> An Integrated Mixed-Integer Programming Model to Address Concurrent 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 can provide more flexibility to the project scheduling problem, as the project execution costs can be enhanced. Hence, the issue has been taken into account in this paper. To do so, a mixed-integer mathematical model is developed which considers the aforementioned flexibility, in addition to the materials quantity discount and space availability restrictions. Moreover, the activities duration has been treated as decision variables. Finally, the efficiency of the proposed model is tested by different instances. Additionally, the influence of the aforementioned parameters is investigated on the model performance. <p class="card-text"><strong>Keywords:</strong> <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%20scheduling" title=" project scheduling"> project scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=quantity%20discount" title=" quantity discount"> quantity discount</a>, <a href="https://publications.waset.org/abstracts/search?q=space%20availability" title=" space availability"> space availability</a> </p> <a href="https://publications.waset.org/abstracts/40331/an-integrated-mixed-integer-programming-model-to-address-concurrent-project-scheduling-and-material-ordering" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/40331.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">367</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">7892</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">7891</span> Cooperative Cross Layer Topology for Concurrent Transmission Scheduling Scheme in Broadband Wireless Networks</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Gunasekaran%20Raja">Gunasekaran Raja</a>, <a href="https://publications.waset.org/abstracts/search?q=Ramkumar%20Jayaraman"> Ramkumar Jayaraman</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In this paper, we consider CCL-N (Cooperative Cross Layer Network) topology based on the cross layer (both centralized and distributed) environment to form network communities. Various performance metrics related to the IEEE 802.16 networks are discussed to design CCL-N Topology. In CCL-N topology, nodes are classified as master nodes (Master Base Station [MBS]) and serving nodes (Relay Station [RS]). Nodes communities are organized based on the networking terminologies. Based on CCL-N Topology, various simulation analyses for both transparent and non-transparent relays are tabulated and throughput efficiency is calculated. Weighted load balancing problem plays a challenging role in IEEE 802.16 network. CoTS (Concurrent Transmission Scheduling) Scheme is formulated in terms of three aspects – transmission mechanism based on identical communities, different communities and identical node communities. CoTS scheme helps in identifying the weighted load balancing problem. Based on the analytical results, modularity value is inversely proportional to that of the error value. The modularity value plays a key role in solving the CoTS problem based on hop count. The transmission mechanism for identical node community has no impact since modularity value is same for all the network groups. In this paper three aspects of communities based on the modularity value which helps in solving the problem of weighted load balancing and CoTS are discussed. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=cross%20layer%20network%20topology" title="cross layer network topology">cross layer network topology</a>, <a href="https://publications.waset.org/abstracts/search?q=concurrent%20scheduling" title=" concurrent scheduling"> concurrent scheduling</a>, <a href="https://publications.waset.org/abstracts/search?q=modularity%20value" title=" modularity value"> modularity value</a>, <a href="https://publications.waset.org/abstracts/search?q=network%20communities%20and%20weighted%20load%20balancing" title=" network communities and weighted load balancing"> network communities and weighted load balancing</a> </p> <a href="https://publications.waset.org/abstracts/48858/cooperative-cross-layer-topology-for-concurrent-transmission-scheduling-scheme-in-broadband-wireless-networks" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/48858.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">265</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">7890</span> Dynamic Construction Site Layout Using Ant Colony Optimization</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Yassir%20AbdelRazig">Yassir AbdelRazig</a> </p> <p class="card-text"><strong>Abstract:</strong></p> Evolutionary optimization methods such as genetic algorithms have been used extensively for the construction site layout problem. More recently, ant colony optimization algorithms, which are evolutionary methods based on the foraging behavior of ants, have been successfully applied to benchmark combinatorial optimization problems. This paper proposes a formulation of the site layout problem in terms of a sequencing problem that is suitable for solution using an ant colony optimization algorithm. In the construction industry, site layout is a very important planning problem. The objective of site layout is to position temporary facilities both geographically and at the correct time such that the construction work can be performed satisfactorily with minimal costs and improved safety and working environment. During the last decade, evolutionary methods such as genetic algorithms have been used extensively for the construction site layout problem. This paper proposes an ant colony optimization model for construction site layout. A simple case study for a highway project is utilized to illustrate the application of the model. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=ant%20colony" title="ant colony">ant colony</a>, <a href="https://publications.waset.org/abstracts/search?q=construction%20site%20layout" title=" construction site layout"> construction site layout</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=genetic%20algorithms" title=" genetic algorithms"> genetic algorithms</a> </p> <a href="https://publications.waset.org/abstracts/28641/dynamic-construction-site-layout-using-ant-colony-optimization" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/28641.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">383</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">7889</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">7888</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">331</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">7887</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">7886</span> Two Points Crossover Genetic Algorithm for Loop Layout Design Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Xu%20LiYun">Xu LiYun</a>, <a href="https://publications.waset.org/abstracts/search?q=Briand%20Florent"> Briand Florent</a>, <a href="https://publications.waset.org/abstracts/search?q=Fan%20GuoLiang"> Fan GuoLiang</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The loop-layout design problem (LLDP) aims at optimizing the sequence of positioning of the machines around the cyclic production line. Traffic congestion is the usual criteria to minimize in this type of problem, i.e. the number of additional cycles spent by each part in the network until the completion of its required routing sequence of machines. This paper aims at applying several improvements mechanisms such as a positioned-based crossover operator for the Genetic Algorithm (GA) called a Two Points Crossover (TPC) and an offspring selection process. The performance of the improved GA is measured using well-known examples from literature and compared to other evolutionary algorithms. Good results show that GA can still be competitive for this type of problem against more recent evolutionary algorithms. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=crossover" title="crossover">crossover</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=layout%20design%20problem" title=" layout design problem"> layout design problem</a>, <a href="https://publications.waset.org/abstracts/search?q=loop-layout" title=" loop-layout"> loop-layout</a>, <a href="https://publications.waset.org/abstracts/search?q=manufacturing%20optimization" title=" manufacturing optimization"> manufacturing optimization</a> </p> <a href="https://publications.waset.org/abstracts/75351/two-points-crossover-genetic-algorithm-for-loop-layout-design-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/75351.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">279</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">7885</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">7884</span> Reinforcement Learning For Agile CNC Manufacturing: Optimizing Configurations And Sequencing</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Huan%20Ting%20Liao">Huan Ting Liao</a> </p> <p class="card-text"><strong>Abstract:</strong></p> In a typical manufacturing environment, computer numerical control (CNC) machining is essential for automating production through precise computer-controlled tool operations, significantly enhancing efficiency and ensuring consistent product quality. However, traditional CNC production lines often rely on manual loading and unloading, limiting operational efficiency and scalability. Although automated loading systems have been developed, they frequently lack sufficient intelligence and configuration efficiency, requiring extensive setup adjustments for different products and impacting overall productivity. This research addresses the job shop scheduling problem (JSSP) in CNC machining environments, aiming to minimize total completion time (makespan) and maximize CNC machine utilization. We propose a novel approach using reinforcement learning (RL), specifically the Q-learning algorithm, to optimize scheduling decisions. The study simulates the JSSP, incorporating robotic arm operations, machine processing times, and work order demand allocation to determine optimal processing sequences. The Q-learning algorithm enhances machine utilization by dynamically balancing workloads across CNC machines, adapting to varying job demands and machine states. This approach offers robust solutions for complex manufacturing environments by automating decision-making processes for job assignments. Additionally, we evaluate various layout configurations to identify the most efficient setup. By integrating RL-based scheduling optimization with layout analysis, this research aims to provide a comprehensive solution for improving manufacturing efficiency and productivity in CNC-based job shops. The proposed method's adaptability and automation potential promise significant advancements in tackling dynamic manufacturing challenges. <p class="card-text"><strong>Keywords:</strong> <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=reinforcement%20learning" title=" reinforcement learning"> reinforcement learning</a>, <a href="https://publications.waset.org/abstracts/search?q=operations%20sequence" title=" operations sequence"> operations sequence</a>, <a href="https://publications.waset.org/abstracts/search?q=layout%20optimization" title=" layout optimization"> layout optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=q-learning" title=" q-learning"> q-learning</a> </p> <a href="https://publications.waset.org/abstracts/192009/reinforcement-learning-for-agile-cnc-manufacturing-optimizing-configurations-and-sequencing" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/192009.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">24</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">7883</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">7882</span> A Clustering-Sequencing Approach to the Facility Layout Problem</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Saeideh%20Salimpour">Saeideh Salimpour</a>, <a href="https://publications.waset.org/abstracts/search?q=Sophie-Charlotte%20Viaux"> Sophie-Charlotte Viaux</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Azab"> Ahmed Azab</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20Fazle%20Baki"> Mohammed Fazle Baki</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The Facility Layout Problem (FLP) is key to the efficient and cost-effective operation of a system. This paper presents a hybrid heuristic- and mathematical-programming-based approach that divides the problem conceptually into those of clustering and sequencing. First, clusters of vertically aligned facilities are formed, which are later on sequenced horizontally. The developed methodology provides promising results in comparison to its counterparts in the literature by minimizing the inter-distances for facilities which have more interactions amongst each other and aims at placing the facilities with more interactions at the centroid of the shop. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=clustering-sequencing%20approach" title="clustering-sequencing approach">clustering-sequencing approach</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=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=unequal%20facility%20layout%20problem" title=" unequal facility layout problem"> unequal facility layout problem</a> </p> <a href="https://publications.waset.org/abstracts/58494/a-clustering-sequencing-approach-to-the-facility-layout-problem" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/58494.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">333</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">7881</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">7880</span> Identification of Promising Infant Clusters to Obtain Improved Block Layout Designs </h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Mustahsan%20Mir">Mustahsan Mir</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20Hassanin"> Ahmed Hassanin</a>, <a href="https://publications.waset.org/abstracts/search?q=Mohammed%20A.%20Al-Saleh"> Mohammed A. Al-Saleh</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The layout optimization of building blocks of unequal areas has applications in many disciplines including VLSI floorplanning, macrocell placement, unequal-area facilities layout optimization, and plant or machine layout design. A number of heuristics and some analytical and hybrid techniques have been published to solve this problem. This paper presents an efficient high-quality building-block layout design technique especially suited for solving large-size problems. The higher efficiency and improved quality of optimized solutions are made possible by introducing the concept of Promising Infant Clusters in a constructive placement procedure. The results presented in the paper demonstrate the improved performance of the presented technique for benchmark problems in comparison with published heuristic, analytic, and hybrid techniques. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=block%20layout%20problem" title="block layout problem">block layout problem</a>, <a href="https://publications.waset.org/abstracts/search?q=building-block%20layout%20design" title=" building-block layout design"> building-block layout design</a>, <a href="https://publications.waset.org/abstracts/search?q=CAD" title=" CAD"> CAD</a>, <a href="https://publications.waset.org/abstracts/search?q=optimization" title=" optimization"> optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=search%20techniques" title=" search techniques"> search techniques</a> </p> <a href="https://publications.waset.org/abstracts/38727/identification-of-promising-infant-clusters-to-obtain-improved-block-layout-designs" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/38727.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">386</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">7879</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">7878</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">7877</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">7876</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">7875</span> Multi-Criteria Decision Making Approaches for Facility Planning Problem Evaluation: A Survey</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20M.%20El-Araby">Ahmed M. El-Araby</a>, <a href="https://publications.waset.org/abstracts/search?q=Ibrahim%20Sabry"> Ibrahim Sabry</a>, <a href="https://publications.waset.org/abstracts/search?q=Ahmed%20El-Assal"> Ahmed El-Assal</a> </p> <p class="card-text"><strong>Abstract:</strong></p> The relationships between the industrial facilities, the capacity available for these facilities, and the costs involved are the main factors in deciding the correct selection of a facility layout. In general, an issue of facility layout is considered to be an unstructured problem of decision-making. The objective of this work is to provide a survey that describes the techniques by which a facility planning problem can be solved and also the effect of these techniques on the efficiency of the layout. The multi-criteria decision making (MCDM) techniques can be classified according to the previous researches into three categories which are the use of single MCDM, combining two or more MCDM, and the integration of MCDM with another technique such as genetic algorithms (GA). This paper presents a review of different multi-criteria decision making (MCDM) techniques that have been proposed in the literature to pick the most suitable layout design. These methods are particularly suitable to deal with complex situations, including various criteria and conflicting goals which need to be optimized simultaneously. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=facility%20layout" title="facility layout">facility layout</a>, <a href="https://publications.waset.org/abstracts/search?q=MCDM" title=" MCDM"> MCDM</a>, <a href="https://publications.waset.org/abstracts/search?q=GA" title=" GA"> GA</a>, <a href="https://publications.waset.org/abstracts/search?q=literature%20review" title=" literature review"> literature review</a> </p> <a href="https://publications.waset.org/abstracts/136799/multi-criteria-decision-making-approaches-for-facility-planning-problem-evaluation-a-survey" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/136799.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">7874</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">7873</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">34</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">7872</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">7871</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">450</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">7870</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">7869</span> An Improved GA to Address Integrated Formulation of Project Scheduling and Material Ordering with Discount Options</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 the resource constraint project scheduling and material ordering problems have received significant attention within the last decades. Hence, the issue has been investigated here with the aim to minimize total project costs. Furthermore, the presented model considers different discount options in order to approach the real world conditions. The incorporated alternatives consist of all-unit and incremental discount strategies. On the other hand, a modified version of the genetic algorithm is applied in order to solve the model for larger sizes, in particular. Finally, the applicability and efficiency of the given model is tested by different numerical instances. <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=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/51823/an-improved-ga-to-address-integrated-formulation-of-project-scheduling-and-material-ordering-with-discount-options" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/51823.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">302</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">7868</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">7867</span> Research on the Optimization of the Facility Layout of Efficient Cafeterias for Troops</h5> <div class="card-body"> <p class="card-text"><strong>Authors:</strong> <a href="https://publications.waset.org/abstracts/search?q=Qing%20Zhang">Qing Zhang</a>, <a href="https://publications.waset.org/abstracts/search?q=Jiachen%20Nie"> Jiachen Nie</a>, <a href="https://publications.waset.org/abstracts/search?q=Yujia%20Wen"> Yujia Wen</a>, <a href="https://publications.waset.org/abstracts/search?q=Guanyuan%20Kou"> Guanyuan Kou</a>, <a href="https://publications.waset.org/abstracts/search?q=Peng%20Yu"> Peng Yu</a>, <a href="https://publications.waset.org/abstracts/search?q=Kun%20Xia"> Kun Xia</a>, <a href="https://publications.waset.org/abstracts/search?q=Qin%20Yang"> Qin Yang</a>, <a href="https://publications.waset.org/abstracts/search?q=Li%20Ding"> Li Ding</a> </p> <p class="card-text"><strong>Abstract:</strong></p> BACKGROUND: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. OBJECTIVE: This article tried to optimize the layout of troops’ cafeteria and to improve the overall efficiency of the dining process. METHODS: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. RESULTS: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p<0.0001, p=0.0001) compared with the other two layouts, while troops-flow density and interference both greatly reduced in the two new layouts. In the experiment, process completing time and the number of interference reduced as well, which verified corresponding simulation results. CONCLUSIONS: Our two new layout schemes are tested to be optimal by a series of simulation and space experiments. In future research, similar approaches could be applied when taking layout-design algorithm calculation into consideration. <p class="card-text"><strong>Keywords:</strong> <a href="https://publications.waset.org/abstracts/search?q=layout%20optimization" title="layout optimization">layout optimization</a>, <a href="https://publications.waset.org/abstracts/search?q=dining%20efficiency" title=" dining efficiency"> dining efficiency</a>, <a href="https://publications.waset.org/abstracts/search?q=troops%E2%80%99%20cafeteria" title=" troops’ cafeteria"> troops’ cafeteria</a>, <a href="https://publications.waset.org/abstracts/search?q=anylogic%20simulation" title=" anylogic simulation"> anylogic simulation</a>, <a href="https://publications.waset.org/abstracts/search?q=field%20experiment" title=" field experiment"> field experiment</a> </p> <a href="https://publications.waset.org/abstracts/143500/research-on-the-optimization-of-the-facility-layout-of-efficient-cafeterias-for-troops" class="btn btn-primary btn-sm">Procedia</a> <a href="https://publications.waset.org/abstracts/143500.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">143</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">7866</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 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