On the landscape of combinatorial optimization problems

Tayarani-N, M.-H. and Prügel-Bennett, A. (2014) On the landscape of combinatorial optimization problems. IEEE Transactions on Evolutionary Computation, 18(3), pp. 420-434. (doi: 10.1109/TEVC.2013.2281502)

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Abstract

This paper carries out a comparison of the fitness landscape for four classic optimization problems: Max-Sat, graph-coloring, traveling salesman, and quadratic assignment. We have focused on two types of properties, local average properties of the landscape, and properties of the local optima. For the local optima we give a fairly comprehensive description of the properties, including the expected time to reach a local optimum, the number of local optima at different cost levels, the distance between optima, and the expected probability of reaching the optima. Principle component analysis is used to understand the correlations between the local optima. Most of the properties that we examine have not been studied previously, particularly those concerned with properties of the local optima. We compare and contrast the behavior of the four different problems. Although the problems are very different at the low level, many of the long-range properties exhibit a remarkable degree of similarity.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Tayarani, Dr Mohammad
Authors: Tayarani-N, M.-H., and Prügel-Bennett, A.
College/School:College of Science and Engineering > School of Computing Science
Journal Name:IEEE Transactions on Evolutionary Computation
Publisher:IEEE
ISSN:1089-778X
ISSN (Online):1941-0026
Published Online:11 September 2013

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