A new hybrid genetic algorithm for job shop scheduling problem
by Marjan Kuchaki Rafsanjani; Milad Riyahi
International Journal of Advanced Intelligence Paradigms (IJAIP), Vol. 16, No. 2, 2020

Abstract: Job shop scheduling problem is an NP-hard problem. This paper proposes a new hybrid genetic algorithm to solve the problem in an appropriate way. In this paper, a new selection criterion to tackle premature convergence problem is introduced. To make full use of the problem itself, a new crossover based on the machines is designed. Furthermore, a new local search is designed which can improve the local search ability of proposed GA. This new approach is run on the some problems and computer simulation shows the effectiveness of the proposed approach.

Online publication date: Fri, 01-May-2020

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 Advanced Intelligence Paradigms (IJAIP):
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