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ENHANCED IMPROVEMENT OF INDIVIDUALS IN GENETIC ALGORITHMS
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BibTeX
@MISC{Misevičius_enhancedimprovement,
author = {Alfonsas Misevičius and Dalius Rubliauskas},
title = {ENHANCED IMPROVEMENT OF INDIVIDUALS IN GENETIC ALGORITHMS},
year = {}
}
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Abstract
Abstract. In this paper, a new modification of the genetic algorithms (GAs) based on an enhanced improvement of individuals is discussed. The basic philosophy of the proposed approach is to accelerate the convergence speed of the genetic search by maintaining compact populations of the outstanding quality individuals – “super-individuals”. The super-individuals are obtained by means of powerful iterated local search techniques. The increase in time for the improvement of individuals is compensated by decreasing the size of populations. We tested our approach on a wellknown combinatorial optimization problem, the quadratic assignment problem (QAP). The results of the experiments show that using the enhanced improvement in GAs makes it possible to achieve very encouraging performance.
Keyphrases
enhanced improvement individual genetic algorithm enhanced improvement basic philosophy genetic search new modification powerful iterated local search technique quadratic assignment problem genetic algorithm wellknown combinatorial optimization problem compact population convergence speed encouraging performance outstanding quality individual super-individuals
