Main effect fine-tuning of the mutation operator and the neighbourhood function for uncapacitated facility location problems

Chan, Kit Yan; Aydin, Mehmet Emin; Fogarty, Terence C.

Abstract

In both genetic algorithms (GAs) and simulated annealing (SA), solutions can be represented by gene representation. Mutation operator in GA and neighborhood function in SA are used to explore the solution space. They usually select genes for performing mutation. The rate of selection of genes can be called mutation rate. However, randomly selecting genes may not be the best way for both algorithms. This paper describes how to estimate the main effect in genes representation. The resulting estimates cannot only be used to understand the domination of gene representation, but also employed to fine-tune the mutation rate in both the mutation operator in the GA and the neighborhood function in the SA. It has been demonstrated the use of the proposed methods for solving uncapacitated facility location problems and discuss the examination of the proposed methods with some useful comparisons with both the latest developed GA and SA for solving this problem. For many well-known benchmark problems, the proposed methods yield better results in solution quality than the previously used methods. © Springer-Verlag 2006.

• Journal Article Type: Article
• Publication Date: Sep 1, 2006
• Journal: Soft Computing
• Print ISSN: 1432-7643
• Electronic ISSN: 1433-7479
• Publisher: Springer (part of Springer Nature)
• Peer Reviewed: Peer Reviewed
• Volume: 10
• Issue: 11
• Pages: 1075-1090
• DOI: https://doi.org/10.1007/s00500-005-0044-4
• Keywords: mutation rate, uncapacitated facility location problem, genetic algorithm, simulated annealing, main effect
• Public URL: https://uwe-repository.worktribe.com/output/1036842
• Publisher URL: http://dx.doi.org/10.1007/s00500-005-0044-4