An empirical study of hybrid genetic algorithms for the set covering problem

An empirical study of hybrid genetic algorithms for the set covering problem

0.00 Avg rating0 Votes
Article ID: iaor20062948
Country: United Kingdom
Volume: 56
Issue: 10
Start Page Number: 1213
End Page Number: 1223
Publication Date: Oct 2005
Journal: Journal of the Operational Research Society
Authors: , ,
Keywords: heuristics
Abstract:

The purpose of this paper is to explore the computational performance of several hybrid algorithms that are extensions of a basic genetic algorithm (GA) approach for solving the set covering problem (SCP). We start by making several enhancements to a GA for the SCP that was proposed by Beasley and Chu. Next, several hybrid solution approaches are introduced that combine the GA with various local neighbourhood search approaches, with a form of the greedy randomized adaptive search procedure, and with an estimation of distribution algorithms approach. Using Beasley's library of SCPs extensive computational results are generated for the hybrid solution approaches defined in this paper. Statistical analyses of the results are performed.

Reviews

Required fields are marked *. Your email address will not be published.