Impact of Fuzzy Logic in the Cooperation of Metaheuristics

Algorithm selection problem is a common problem when we solve optimization problems. To cope with it we have proposed a hybrid system of metaheuristics that intelligently combines different strategies using a coordinator based on Fuzzy Logic. In this paper we study the impact of Fuzzy Logic in the behaviour of this hybrid system. In order to do that we perform some test to study the impact of an important parameter, the α− cut used in the fuzzy engine of the system, demonstrating how the variations on this parameter may change the performance of the system with different kind of instances.

[1]  Carlos Cruz Corona,et al.  Using memory and fuzzy rules in a co-operative multi-thread strategy for optimization , 2006, Inf. Sci..

[2]  John R. Rice,et al.  The Algorithm Selection Problem , 1976, Adv. Comput..

[3]  Ludmila I. Kuncheva,et al.  "Fuzzy" versus "nonfuzzy" in combining classifiers designed by Boosting , 2003, IEEE Trans. Fuzzy Syst..

[4]  F. Glover,et al.  Handbook of Metaheuristics , 2019, International Series in Operations Research & Management Science.

[5]  Iluminada Baturone,et al.  Xfuzzy 3.0: a development environment for fuzzy systems , 2001, EUSFLAT Conf..

[6]  Dana S. Richards,et al.  A Multi-Population Genetic Algorithm for Solving the K-Partition Problem on Hyper-Cubes , 1991, ICGA.

[7]  Cezary Z. Janikow,et al.  Fuzzy decision trees: issues and methods , 1998, IEEE Trans. Syst. Man Cybern. Part B.

[8]  Teodor Gabriel Crainic,et al.  A cooperative parallel meta-heuristic for the vehicle routing problem with time windows , 2005, Comput. Oper. Res..

[9]  Pierre Hansen,et al.  Cooperative Parallel Variable Neighborhood Search for the p-Median , 2004, J. Heuristics.

[10]  M. Carmen Garrido,et al.  A Cooperative System of Metaheuristics , 2007, 7th International Conference on Hybrid Intelligent Systems (HIS 2007).