A comparative study of fuzzy parameter control in a general purpose local search metaheuristic

Jackson, Warren G.; �zcan, Ender; John, Robert I.

Abstract

There is a growing number of studies on general purpose metaheuristics that are directly applicable to multiple domains. Parameter setting is a particular issue considering that many of such search methods come with a set of parameters to be configured. Fuzzy logic has been used extensively in control applications and is known for its ability to handle uncertainty. In this study, we investigate the potential of using fuzzy systems to control the parameter settings of a threshold accepting (TA) metaheuristic for improving the overall effectiveness of a cross-domain approach. We have evaluated the performance of various general purpose local search metaheuristics which mix multiple heuristics at random and apply the TA metaheuristic with fixed threshold, crisp (non-fuzzy) rule-based control of the threshold and various fuzzy systems controlling the threshold. The empirical results show that the approach using the TA with crisp rule-based control performs the best across six problem domains from a benchmark.

Citation

Jackson, W. G., Özcan, E., & John, R. I. (2016, July). A comparative study of fuzzy parameter control in a general purpose local search metaheuristic. Presented at 2016 IEEE Congress on Evolutionary Computation (CEC)

• Conference Name: 2016 IEEE Congress on Evolutionary Computation (CEC)
• Start Date: Jul 24, 2016
• End Date: Jul 29, 2016
• Acceptance Date: Mar 16, 2016
• Publication Date: Jul 29, 2016
• Deposit Date: Aug 31, 2016
• Publicly Available Date: Aug 31, 2016
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1109/CEC.2016.7743787
• Public URL: https://nottingham-repository.worktribe.com/output/798454
• Contract Date: Aug 31, 2016