A multi-objective chemical reaction optimisation algorithm for multi-objective travelling salesman problem
by Samira Bouzoubia; Abdesslem Layeb; Salim Chikhi
International Journal of Innovative Computing and Applications (IJICA), Vol. 6, No. 2, 2014

Abstract: The multi-objective travelling salesman problem (MOTSP) is a well-known combinatorial optimisation problem that belongs to the class of NP-hard problems. The MOTSP plays an important role in computing theory and in many real life applications. Unfortunately, finding efficient MOTSP solutions is still a challenging problem. That is why several methods were proposed to deal with this problem. This paper proposes a new multi-objective chemical reaction optimisation (MOCRO) algorithm to solve MOTSP. To maintain the diversity of the solutions, MOCRO uses a non-dominated sorting procedure proposed in NSGA2. Two new variants of MOCRO are proposed to deal the MOTSP. The first is MOCRO based on amount of domination (MOCRO-Dom), while the second is MOCRO based on weighted sum (MOCRO-WS). The experimental results have shown the superior performance of MOCRO-Dom and MOCRO-WS compared to NSGA2. Moreover, a comparative study between MOCRO-Dom and MOCRO-WS and the impact of the major parameters on the performance has been investigated.

Online publication date: Wed, 31-Dec-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 Innovative Computing and Applications (IJICA):
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