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: | Vasko F.J., Knolle P.J., Spiegel D.S. |
Keywords: | heuristics |
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.