Multi-objective flexible job shop scheduling using hybrid differential evolution algorithm
by G. Balaraju; Sriram Venkatesh; B. Siva Prasad Reddy
International Journal of Internet Manufacturing and Services (IJIMS), Vol. 3, No. 3, 2014

Abstract: The authors addressed multi objective flexible job shop scheduling problems using hybrid differential evolution algorithm for minimisation of makespan, total machine load and critical machine load. The differential evolution algorithm is a stochastic-based adaptive scheme used for global optimisation over continuous space and to apply it for flexible job shop scheduling problem a suitable encoding mechanism is required. In this work random keys encoding mechanism is used to generate schedules that deals with floating point vectors. A non-dominated sorting algorithm is used to find the set of non-dominated solutions for the given scheduling problem. The proposed approach is extensively tested on a set of standard flexible job shop scheduling instances reported in the literature and it is found that the proposed algorithm is performing well on all the test problems.

Online publication date: Mon, 30-Jun-2014

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 Internet Manufacturing and Services (IJIMS):
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