Instance-specific multi-objective parameter tuning based on fuzzy logic
Abstract
Finding good parameter values for meta-heuristics is known as the parameter setting problem. A new parameter tuning strategy, called IPTS, is proposed that is a novel instance-specific method to take the trade-off between solution quality and computational time into consideration. Two important steps in the method are an a priori statistical analysis to identify the factors that determine heuristic performance in both quality and time for a specific type of problem, and the transformation of these insights into a fuzzy inference system rule base which aims to return parameter values on the Pareto-front with respect to a decision maker’s preference.
Applied to the symmetric Travelling Salesman Problem and the meta-heuristic Guided Local Search, the approach is consistently faster than a traditional non-instance-specific parameter tuning strategy without significantly affecting solution quality; optimised for speed, computational times are shown to be on average 20 times faster while producing solutions of similar quality. A number of interesting areas for further research are discussed.
Keywords
Metaheuristics, combinatorial optimisation, traveling salesman problem, parameter setting, fuzzy logic
Date of this Version
2012
DOI
10.1016/j.ejor.2011.10.024
Comments
European Journal of Operational Research, Volume 218, Issue 2, 16 April 2012, Pages 305–315