The analysis of evolutionary optimisation on the TSP(1,2) problem
by Xiaoyun Xia; Xinsheng Lai; Chenfu Yi
International Journal of Computational Science and Engineering (IJCSE), Vol. 18, No. 3, 2019

Abstract: TSP(1,2) problem is a special case of the travelling salesperson problem which is NP-hard. Many heuristics including evolutionary algorithms (EAs) are proposed to solve the TSP(1,2) problem. However, we know little about the performance of the EAs for the TSP(1,2) problem. This paper presents an approximation analysis of the (1+1) EA on this problem. It is shown that both the (1+1) EA and (µ + λ) EA can obtain 3/2 approximation ratio for this problem in expected polynomial runtime O(n3) and O ((µ/λ)n3 + n) , respectively. Furthermore, we prove that the (1+1) EA can provide a much tighter upper bound than a simple ACO on the TSP(1,2) problem.

Online publication date: Tue, 26-Mar-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 Computational Science and Engineering (IJCSE):
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