A hybrid particle swarm optimisation for multi-objective flexible job-shop scheduling problem with dual-resources constrained
by Jing Zhang; Jing Jie; Wanliang Wang; Xinli Xu
International Journal of Computing Science and Mathematics (IJCSM), Vol. 8, No. 6, 2017

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.

Online publication date: Wed, 03-Jan-2018

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computing Science and Mathematics (IJCSM):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com