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In this article, the concept of e-optimal stopping time of a genetic algorithm with elitist model (EGA) has been introduced. The probability of performing mutation plays an important role in the computation of the Î-optimal stopping times. Two approaches, namely, pessimistic and optimistic have been considered here to find out the e-optimal stopping time. It has been found that the total number of strings to be searched in the optimistic approach to obtain e-optimal string is less than the number of all possible strings for sufficiently large string length. This observation validates the use of genetic algorithms in solving complex optimization problems.
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Tom
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91--111
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bibliogr. 29 poz.
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- Machine Intelligence Unit, Indian Statistical Institute, 203 B.T. Road, Calcutta 700 035, India, sankar@isical.ac.in
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bwmeta1.element.baztech-article-BUS1-0003-0061