Research on flexible job shop scheduling problem based on improved discrete particle swarm optimization

Qi Zhang; Bin Zhang; Wen Feng Liang

doi:10.1117/12.2645548

30 August 2022 Research on flexible job shop scheduling problem based on improved discrete particle swarm optimization

Qi Zhang, Bin Zhang, Wen Feng Liang

Proceedings Volume 12309, International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2022); 123092N (2022) https://doi.org/10.1117/12.2645548
Event: International Conference on Advanced Manufacturing Technology and Manufacturing System (ICAMTMS 2022), 2022, Shijiazhuang, China

Abstract

For the flexible job shop scheduling problem with the objective of minimizing the maximum make-time, an adaptive discrete particle swarm algorithm is proposed. The algorithm adopts an initialization method that combines random generation and process-based global load minimum selection machine initialization. At the same time, in order to improve the convergence speed of the algorithm, an adaptive inertia weight is added to the particle position update method, and crossover and mutation operations are introduced. Through comparative experiments and numerical analysis of benchmark examples, the effectiveness of the proposed adaptive hybrid discrete particle swarm optimization algorithm is verified.

Citation Download Citation

Qi Zhang, Bin Zhang, and Wen Feng Liang "Research on flexible job shop scheduling problem based on improved discrete particle swarm optimization", Proc. SPIE 12309, International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2022), 123092N (30 August 2022); https://doi.org/10.1117/12.2645548

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