Swarm-based neighbourhood search for fuzzy job shop scheduling
by You-lian Zheng, Yuan-xiang Li, De-ming Lei
International Journal of Innovative Computing and Applications (IJICA), Vol. 3, No. 3, 2011

Abstract: In this paper, fuzzy job shop scheduling problems are considered and an efficient swarm-based neighbourhood search (SNS) is proposed, in which an ordered operation-based representation and the decoding procedure are given. It is proved that most of possible actual completion times lie in the cut of fuzzy completion time for each job. In SNS, adaptive swap operation and binary tournament selection are applied to update swarm. SNS is compared with some methods from literature and computational results demonstrate that SNS has promising advantage on fuzzy scheduling.

Online publication date: Sat, 21-Mar-2015

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 Innovative Computing and Applications (IJICA):
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