Research on Fuzzy Flexible Job Shop Scheduling Problem Based on Hybrid QPSO

Authors

Junxuan Li, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;
Wang Yan, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;
Zhicheng Ji, Engineering Research Center of Internet of Things Technology Applications Ministry of Education, Wuxi 214122, China;

Abstract

Abstract: To solve the flexible job shop scheduling problem of uncertain processing time, triangular fuzzy numbers are used to characterize the relevant time parameters and a Hybrid Quantum Particle Swarm Optimization (HQPSO) is proposed. On the basis of making full use of the global search capability of Quantum Particle Swarm Optimization, the search efficiency is increased by designing a boundary repair strategy and a cooperative update strategy. Meanwhile, the cross-operator and path relinking technique are used to in the operation sequence mapped by the excellent particles, which makes up the disadvantages of the insufficient ability of deeply exploration of the most continuous algorithms when solving discrete problems. Five classic test examples and an instance of an optical fiber manufacturing workshop are analyzed and show that the proposed method is better than the original QPSO and three other algorithms mentioned in recent literature and has good practical value.

Recommended Citation

Li, Junxuan; Yan, Wang; and Ji, Zhicheng (2020) "Research on Fuzzy Flexible Job Shop Scheduling Problem Based on Hybrid QPSO," Journal of System Simulation: Vol. 32: Iss. 10, Article 19.
DOI: 10.16182/j.issn1004731x.joss.20-FZ0332
Available at: https://dc-china-simulation.researchcommons.org/journal/vol32/iss10/19

First Page

2010

Revised Date

2020-06-10

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.20-FZ0332

Last Page

2021

CLC

TP278

Recommended Citation

Li Junxuan, Wang Yan, Ji Zhicheng. Research on Fuzzy Flexible Job Shop Scheduling Problem Based on Hybrid QPSO[J]. Journal of System Simulation, 2020, 32(10): 2010-2021.

DOI

10.16182/j.issn1004731x.joss.20-FZ0332