Title: A hybrid particle swarm optimisation for multi-objective flexible job-shop scheduling problem with dual-resources constrained
Authors: Jing Zhang; Jing Jie; Wanliang Wang; Xinli Xu
Addresses: Department of Computer and Information Technology, Zhejiang Police College, Hangzhou, China ' College of Automation & Electronic Engineering, Zhejiang University of Science and Technology, Hangzhou, China ' College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China ' College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou, China
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.
Keywords: flexible job shop scheduling problem; FJSP; hybrid discrete particle swarm optimisation; DPSO; dual-resource constrained; multi-objective optimisation.
International Journal of Computing Science and Mathematics, 2017 Vol.8 No.6, pp.526 - 532
Received: 19 May 2016
Accepted: 06 Apr 2017
Published online: 03 Jan 2018 *