Solving Optimization Problem With Particle Swarm Optimization: Solving Hybrid Flow Shop Scheduling Problem With Particle Swarm Optimization Algorithm

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Date

2021

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Volume Title

Publisher

Springer

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Green Open Access

No

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Abstract

The flow shop scheduling problem is widely discussed in the literature since it is frequently applied in real industry. This paper presents a variant of flow shop scheduling problem with parallel machines. The proposed problem includes multistage and identical parallel machines at each stage, and the sequence-dependent setup time and transportation time are considered. The objective function is minimization of makespan. The particle swarm optimization algorithm (PSO) is addressed to solve the problem and compared with genetic algorithm and heuristics. The benchmark instances are generated to demonstrate the performance of the PSO. The numerical results show that the PSO significantly outperforms the comparison set. © 2021 Elsevier B.V., All rights reserved.

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Keywords

Combinatorial Optimization, Hybrid Flow Shop, Makespan, Particle Swarm Optimization

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N/A

Scopus Q

Q4
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OpenCitations Citation Count
2

Source

International Series in Operations Research and Management Science

Volume

306

Issue

Start Page

263

End Page

277
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3

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