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An Effective Hybrid Particle Swarm Optimization Algorithm for Multi-objective FJSP

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Effective Methods for Integrated Process Planning and Scheduling

Part of the book series: Engineering Applications of Computational Methods ((EACM,volume 2))

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Abstract

Flexible Job shop Scheduling Problem (FJSP) is an extension of the classical job shop scheduling problem. Although the traditional optimization algorithms could obtain preferable results in solving the mono-objective FJSP, they are very difficult to solve multi-objective FJSP very well. In this chapter, a Particle Swarm Optimization (PSO) algorithm and a Tabu Search (TS) algorithm are combined to solve the multi-objective FJSP with several conflicting and incommensurable objectives. PSO which integrates local search and global search scheme possesses high search efficiency. And TS is a meta-heuristic which is designed for finding a near-optimal solution of combinatorial optimization problems. Through reasonably hybridizing the two optimization algorithms, an effective hybrid approach for the multi-objective FJSP has been proposed. The computational results have proved that the proposed hybrid algorithm is an efficient and effective approach to solve the multi-objective FJSP, especially for the problems on a large scale.

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Authors and Affiliations

  1. School of Mechanical Science and Engineering, HUST, State Key Laboratory of Digital Manufacturing and Equipment Technology, Wuhan, Hubei, China

    Xinyu Li

  2. School of Mechanical Science and Engineering, HUST, State Key Laboratory of Digital Manufacturing and Equipment Technology, Wuhan, Hubei, China

    Liang Gao

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  1. Xinyu Li
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  2. Liang Gao
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Correspondence to Xinyu Li .

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Li, X., Gao, L. (2020). An Effective Hybrid Particle Swarm Optimization Algorithm for Multi-objective FJSP. In: Effective Methods for Integrated Process Planning and Scheduling. Engineering Applications of Computational Methods, vol 2. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-55305-3_13

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  • DOI: https://doi.org/10.1007/978-3-662-55305-3_13

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-55303-9

  • Online ISBN: 978-3-662-55305-3

  • eBook Packages: EngineeringEngineering (R0)

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