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Research Article Peer ReviewedAt least two reviewers Open Access

Dual-Resource Constrained Flexible Job Shop Scheduling Problem with Weighted Superposition Attraction Algorithm

1Abdullah Gül University
2Dokuz Eylül University
✉ Corresponding author: Fatma Selen MADENOĞLU · selen.madenoglu@agu.edu.tr
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Abstract

Flexible job shop scheduling problem (FJSSP) contains two sub-problems, that is, routing and scheduling. Each operation is assigned to a machine among a set of alternative machines in the routing sub-problem, whereas the assigned operations on all machines are sequenced in the scheduling sub-problem to construct a feasible schedule. The operations cannot be processed without a qualified worker, but the worker constraint is usually ignored in the literature. The FJSSP which also considers the worker resource constraints is called the dual resource constrained FJSSP. Dual resource constrained FJSSP deals with machine assignment, order sequencing and worker assignment all together. Weighted Superposition Attraction (WSA), a recent metaheuristic approach is based on two basic mechanisms, ‘superposition’ and ‘attracted movement of agents’ for solving complex optimization problems algorithm is proposed to solve the dual resource constrained FJSSP with makespan minimization. Computational experiments performed in order to test the performance of the proposed WSA algorithm. The result of the WSA algorithm is compared with the results of the dispatching rule based approaches and greedy randomized adaptive search algorithm. The obtained results show that the WSA based algorithm is able to provide good quality solutions in reasonable time limits.

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Cite this article

MADENOĞLU, F. S., & BAYKASOĞLU, A. (2019). Dual-Resource Constrained Flexible Job Shop Scheduling Problem with Weighted Superposition Attraction Algorithm. In International Congress on Human-Computer Interaction, Optimization and Robotic Applications (pp. 167–170). SET Technology. https://doi.org/10.36287/setsci.4.5.033

Article History

Published
12 Oct 2019

License

© 2019 SET Technology. This article is distributed under the terms of the CC BY 4.0.

Research Contributions (2019+)Peer reviewed by at least two reviewers
Open AccessCC BY 4.0
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