Research on FJSP of Improved Particle Swarm Optimization Algorithm Considering Transportation Time

Authors

Chen Kui, School of Information Engineering, Ningxia University, Yinchuan 750021, China;
Bi Li, School of Information Engineering, Ningxia University, Yinchuan 750021, China;

Abstract

Abstract: In the actual FJSP(Flexible Job-shop Scheduling Problem) production environment, there is not only the processing time of the workpiece, but also the transport time of the workpiece between the machines, so the flexible job shop scheduling considering the transport time is more practically significant. A hybrid discrete particle swarm optimization algorithm is proposed to solve the flexible job-shop scheduling problem considering transport time. Aiming at the instability and precocity of particle swarm optimization algorithm, the neighborhood search algorithm is applied to improve its stability, and the combination of competitive learning mechanism and random restart algorithm are introduced to avoid the precocity of pso algorithm. By comparing recent similar algorithms, the feasibility and effectiveness of the hybrid discrete particle swarm optimization algorithm for FJSP with transport time is proved.

Recommended Citation

Kui, Chen and Li, Bi (2021) "Research on FJSP of Improved Particle Swarm Optimization Algorithm Considering Transportation Time," Journal of System Simulation: Vol. 33: Iss. 4, Article 11.
DOI: 10.16182/j.issn1004731x.joss.19-0672
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss4/11

First Page

845

Revised Date

2020-04-17

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.19-0672

Last Page

853

CLC

TP391.9

Recommended Citation

Chen Kui, Bi Li. Research on FJSP of Improved Particle Swarm Optimization Algorithm Considering Transportation Time[J]. Journal of System Simulation, 2021, 33(4): 845-853.

DOI

10.16182/j.issn1004731x.joss.19-0672