Research on dynamic flexible job shop scheduling problem based on discrete particle swarm optimization with readjustment strategy

Qi Zhang; Bin Zhang

doi:10.1117/12.3046596

27 September 2024 Research on dynamic flexible job shop scheduling problem based on discrete particle swarm optimization with readjustment strategy

Qi Zhang, Bin Zhang

Author Affiliations +

Proceedings Volume 13261, Tenth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2024); 132614G (2024) https://doi.org/10.1117/12.3046596
Event: 10th International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2024), 2024, Wuhan, China

Abstract

This paper which is based on previous research proposes a scheduling algorithm which contains Discrete Particle Swarm Optimization and readjustment strategy (RS-DPSO) for dynamic flexible job shop scheduling problems (DFJSP) taking into the new workpieces arrival. This proposed algorithm divides FJSP in dynamic environment into several continuous scheduling subintervals and sets readjustment mechanism which is activated when the new workpieces arrives. DPSO algorithm is used to obtain the appropriate scheduling scheme which meets the requirements of dynamic environment for every subintervals. The feasibility and effectiveness of the proposed algorithm is verified by applying it to a practical case for the DFJSP taking into the new workpieces arrival.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Qi Zhang and Bin Zhang "Research on dynamic flexible job shop scheduling problem based on discrete particle swarm optimization with readjustment strategy", Proc. SPIE 13261, Tenth International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2024), 132614G (27 September 2024); https://doi.org/10.1117/12.3046596

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