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Title of Journal: Soft Computing

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Abbravation: Soft Computing

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Springer-Verlag

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10.1007/s11414-015-9490-7

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1432-7643

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Fuzzy adaptive genetic algorithms design taxonom

Authors: F Herrera M Lozano
Publish Date: 2003/07/14
Volume: 7, Issue: 8, Pages: 545-562
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Abstract

The genetic algorithm behaviour is determined by the exploitation and exploration relationship kept throughout the run Adaptive genetic algorithms that dynamically adjust selected control parameters or genetic operators during the evolution have been built Their objective is to offer the most appropriate exploration and exploitation behaviour to avoid the premature convergence problem and improve the final results One of the adaptive approaches are the adaptive parameter setting techniques based on the use of fuzzy logic controllers the fuzzy adaptive genetic algorithms FAGAs In this paper we analyse the FAGAs in depth First we describe the steps for their design and present an instance which is studied from an empirical point of view Then we propose a taxonomy for FAGAs attending on the combination of two aspects the level where the adaptation takes place and the way the RuleBases are obtained Furthermore FAGAs belonging to different groups of the taxonomy are reviewed Finally we identify some open issues and summarise a few new promising research directions on the topic From the results provided by the approaches presented in the literature and the experimental results achieved in this paper an important conclusion is obtained the use of fuzzy logic controllers to adapt genetic algorithm parameters may really improve the genetic algorithm performance

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