Title: An empirical evaluation of memory less and memory using meta-heuristics for solving travelling salesman problem

Authors: Arun Prakash Agrawal; Arvinder Kaur

Addresses: Department of Computer Science and Engineering, Amity School of Engineering and Technology, Amity University, Uttar Pradesh Noida, India ' University School of Information and Communication Technology, Guru Gobind Singh Indraprastha University, New Delhi, India

Abstract: In many situations, a researcher gets bewildered when it comes to selection of an appropriate meta-heuristic algorithm for any specific problem. Meta-heuristic algorithms need to be categorised depending on their ability to solve problems of varying degree of complexity to overpower such confusion. Considering this view, the performance evaluations of six popular meta-heuristic algorithms have been done. Three research questions are framed to evaluate the hypothesis for any difference in the performance of memory less and memory based meta-heuristics. The domain of inquiry in this paper is the travelling salesman problem. Extensive experiments are conducted and results are analysed using various statistical tests such as F-test, and post-hoc tests. An obvious outcome of this study is that there is an interaction effect between the problem sizes and the meta-heuristic used and no clear superiority of one meta-heuristic over the other.

Keywords: optimisation problems; computational intelligence; memory less metaheuristics; memory using meta-heuristics; travelling salesman problem; N-P complete problems; nature inspired optimisation.

DOI: 10.1504/IJCSYSE.2017.089208

International Journal of Computational Systems Engineering, 2017 Vol.3 No.4, pp.228 - 236

Received: 19 Oct 2016
Accepted: 06 Jun 2017

Published online: 09 Jan 2018 *

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