The effect of multiple optima on the simple GA run-time complexity |
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| Authors: | Haldun Aytug Gary J. Koehler |
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| Affiliation: | Decision and Information Sciences, 351 BUS, The Warrington College of Business Administration, University of Florida, Gainesville, FL 32611, United States |
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| Abstract: | Genetic algorithms are stochastic search algorithms that have been applied to optimization problems. In this paper we analyze the run-time complexity of a genetic algorithm when we are interested in one of a set of distinguished solutions. One such case occurs when multiple optima exist. We define the worst case scenario and derive a probabilistic worst case bound on the number of iterations required to find one of these multiple solutions of interest. |
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| Keywords: | Genetic algorithms Markov chains Worst-case analysis |
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