Vehicle configuration design with a packing genetic algorithm
by Yi Miao, Georges M. Fadel, Vladimir B. Gantovnik
International Journal of Heavy Vehicle Systems (IJHVS), Vol. 15, No. 2/3/4, 2008

Abstract: 3D packing problems occur in many applications. Exhaustive search methods cannot identify an optimum packing in reasonable time. To improve the search efficiency of such problems, a packing Genetic Algorithm (GA) with a new encoding method and packing GA operators is proposed. The method is applied to a vehicle configuration design problem, in which the goal is to maximise the vehicle survivability, maintainability and minimise vehicle rollover tendency by finding optimal positions of vehicle components. The packing GA is integrated with a Multi-Objective Genetic Algorithm (MOGA) to search for a non-dominated front, which offers trade-off solutions to the designer.

Online publication date: Wed, 24-Dec-2008

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 Heavy Vehicle Systems (IJHVS):
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