Two-sided assembly line car sequencing with a fuzzy adaptive extended coincidence algorithm
by Parames Chutima; Watcharawit Tanontong
International Journal of Industrial and Systems Engineering (IJISE), Vol. 32, No. 1, 2019

Abstract: The car sequencing problem is a constraint satisfaction problem that has attracted the attention of academia and practitioners for many years now. In this paper, the industrial version of the car sequencing problem is extended to reflect more real operations in practice by using a two-sided assembly line instead of classical single-sided one. The fuzzy adaptive extended coincidence algorithm (COIN-F) is developed to optimise the multi-objective car sequencing problem in a Pareto sense. The relative performance of COIN-F is compared against COIN-E, NSGA-II and DPSO. Experimental results demonstrate the effectiveness of COIN-F over the contestant algorithms, especially in the search for the approximate true-Pareto frontier.

Online publication date: Wed, 22-May-2019

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 Industrial and Systems Engineering (IJISE):
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