Tracking Extrema in Dynamic Fitness Functions with Dissortative Mating Genetic Algorithms


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… (More)
DOI: 10.1109/HIS.2008.52


6 Figures and Tables

Slides referencing similar topics