Adapting the artificial bee colony metaheuristic to solve multi-objective problems
by Saima Dhouib; Souhail Dhouib; Habib Chabchoub
International Journal of Manufacturing Technology and Management (IJMTM), Vol. 29, No. 5/6, 2015

Abstract: In this paper, an artificial bee colony (ABC) metaheuristic is adapted to find Pareto optimal set solutions for goal programming problems. The proposed algorithm is named weighted goal programming artificial bee colony (WGP-ABC). This WGP-ABC is personalised to support the MOO by means of a weighted sum formulation for the objective function: solving several scalarisations of the objective function according to a weight vector with non-negative components. The efficiency of the proposed approach is demonstrated by nonlinear engineering design problems. In all problems, multiple solutions to the goal programming problem are found in short computational time using very few user-defined parameters.

Online publication date: Mon, 17-Aug-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 Manufacturing Technology and Management (IJMTM):
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