A hybrid particle swarm optimisation for multi-objective flexible job-shop scheduling problem with dual-resources constrained. (2017)

• Record Type: Journal Article
• Authors: Zhang, Jing; Jie, Jing; Wang, Wanliang; Xu, Xinli
• Is Part Of: International journal of computing science and mathematics. Volume 8:Number 6(2017)
• Page Start: 526
• Page End: 532
• Publication Date: 2017
• Subjects: flexible job shop scheduling problem -- FJSP -- hybrid discrete particle swarm optimisation -- DPSO -- dual-resource constrained -- multi-objective optimisation; Mathematics -- Periodicals; Computer science -- Periodicals; Mathematics -- Data processing -- Periodicals; 510.285
• Languages: English
• ISSNs: 1752-5055

Abstract

In this paper, a hybrid discrete particle swarm algorithm based on maximum fitness function is proposed for a dual-resources constrained flexible job shop scheduling problem with multiple optimisation objectives. An improved position updating mechanism of particles is used to effectively avoid the occurrence of infeasible solution. Additionally, a novel dynamic search strategy is designed to enhance the local exploiting search ability of discrete particle swarms. Finally, simulation results demonstrate that the proposed algorithm effectively decreases both the production time and production cost.