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Author Francesca, Gianpiero ♦ Pellegrini, Paola ♦ Stützle, Thomas ♦ Birattari, Mauro
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword On-line Tuning ♦ Memetic Algorithm ♦ Operator Selection ♦ Parameter Setting ♦ Whole Run ♦ Solution Process ♦ Appropriate Configuration ♦ Optimization Algorithm ♦ Several Recent Study ♦ Appropriate Parameter Configuration ♦ Off-line Tuning ♦ Evolutionary Algorithm ♦ Instance-per-instance Basis ♦ Quadratic Assignment Problem
Abstract Tuning methods for selecting appropriate parameter configurations of optimization algorithms have been the object of several recent studies. The selection of the appropriate configuration may strongly impact on the performance of evolutionary algorithms. In this paper, we study the performance of three memetic algorithms for the quadratic assignment problem when their parameters are tuned either off-line or on-line. Off-line tuning selects a priori one configuration to be used throughout the whole run for all the instances to be tackled. On-line tuning selects the configuration during the solution process, adapting parameter settings on an instance-per-instance basis, and possibly to each phase of the search. The results suggest that off-line tuning achieves a better performance than on-line tuning.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Publisher Date 2011-01-01