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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Publisher
Springer
Open Access Color
Green Open Access
No
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No
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

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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Scopus : 3
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Mendeley Readers : 8
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3
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6
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