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\iteman{io-port 06066848}
\itemau{Ries, Jana; Beullens, Patrick; Salt, David}
\itemti{Instance-specific multi-objective parameter tuning based on fuzzy logic.}
\itemso{Eur. J. Oper. Res. 218, No. 2, 305-315 (2012).}
\itemab
Summary: 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.
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\itemcc{}
\itemut{metaheuristics; combinatorial optimisation; travelling salesman problem; parameter setting; fuzzy logic}
\itemli{doi:10.1016/j.ejor.2011.10.024}
\end