An improved discrete particle swarm optimization for multi-objective flexible job shop scheduling problem under dynamic perturbation

Haoliang Jin; Qibing Jin; Yang Zhang

doi:10.1117/12.2686458

10 August 2023 An improved discrete particle swarm optimization for multi-objective flexible job shop scheduling problem under dynamic perturbation

Haoliang Jin, Qibing Jin, Yang Zhang

Author Affiliations +

Proceedings Volume 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023); 127591G (2023) https://doi.org/10.1117/12.2686458
Event: 2023 3rd International Conference on Automation Control, Algorithm and Intelligent Bionics (ACAIB 2023), 2023, Xiamen, China

Abstract

This paper proposes a novel, improved discrete particle swarm optimization algorithm (IDPSO) to solve the multiobjective flexible job shop scheduling problem (MOFJSP) under dynamic perturbations. Firstly, the idea of variable neighborhood search (VNS) is fused to design three neighborhood structures to enhance the ability of the discrete particle swarm algorithm to jump out of local extremes. Secondly, a non-linear descent inertia weight is designed to help the DPSO algorithm better balance the global and local search capabilities. Furthermore, this paper redesigns the individual optimal as well as global optimal particle update methods of the algorithm for the characteristics of the MOFJSP problem. Then, an external archival solution set of elite strategies is designed to store the non-dominated solutions in the algorithm's solution process. Finally, the effectiveness of this algorithm is verified on the Kacem dataset; compared with other algorithms, the results show that this algorithm has a strong performance in finding the best.

Citation Download Citation

Haoliang Jin, Qibing Jin, and Yang Zhang "An improved discrete particle swarm optimization for multi-objective flexible job shop scheduling problem under dynamic perturbation", Proc. SPIE 12759, International Conference on Automation Control, Algorithm, and Intelligent Bionics (ACAIB 2023), 127591G (10 August 2023); https://doi.org/10.1117/12.2686458

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