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

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Applying Particle Swarm Optimization

Part of the book series: International Series in Operations Research & Management Science ((ISOR,volume 306))

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.

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  1. Abdullah Gül University, Kayseri, Turkey

    Fatma Selen Madenoğlu

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  1. Fatma Selen Madenoğlu
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Correspondence to Fatma Selen Madenoğlu .

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  1. Faculty of Transportation and Logistics, Istanbul University, Avcılar/Istanbul, Turkey

    Burcu Adıgüzel Mercangöz

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Madenoğlu, F.S. (2021). Solving Optimization Problem with Particle Swarm Optimization: Solving Hybrid Flow Shop Scheduling Problem with Particle Swarm Optimization Algorithm. In: Mercangöz, B.A. (eds) Applying Particle Swarm Optimization. International Series in Operations Research & Management Science, vol 306. Springer, Cham. https://doi.org/10.1007/978-3-030-70281-6_14

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