UDC 004.023
1 V.M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine
v.shylo@gmail.com
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TOURNAMENT CROWDING GENETIC ALGORITHMS BASED ON GAUSS MUTATION
Abstract. To solve multimodal optimization problems, a new niching genetic algorithm named tournament crowding genetic algorithm based on Gauss mutation is proposed. A comparative analysis of this algorithm to other crowding algorithms and to parallel hill-climbing algorithm has shown the advantages of the proposed algorithm in many cases. The FPR criterion to estimate the distribution of population elements is proposed and it is shown that computation of this criterion is advisable to estimate algorithms solving multimodal problems of finding global and local maxima.
Keywords: multimodal optimization problem, niching genetic algorithms, crowding algorithms, parallel hill-climbing algorithm, fake peak ratio.
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