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This paper investigates the behavior of the adaptive dissortative mating genetic algorithm (ADMGA) on dynamic problems and compares it with other genetic algorithms (GA). ADMGA is a non-random mating algorithm that selects parents according to their Hamming distance, via a self-adjustable threshold value. The resulting method, by keeping population diversity during the run, provides new means for...
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