In a two-market genetic algorithm applied to a constrained optimization problem, two 'markets' are maintained. One market establishes fitness in terms of the objective function only; the other market measures fitness in terms of the problem constraints only. Previous work on knapsack problems has shown promise for the two-market approach. In this paper we: (1) extend the investigation of two-market GAs to non-linear optimization, (2) introduce a new, two-population variant on the two-market idea, and (3) report on experiments with the two-population, two-market GA that help explain how and why it works. © Springer-Verlag Berlin Heidelberg 2003.
CITATION STYLE
Kimbrough, S. O., Lu, M., Wood, D. H., & Wu, D. J. (2003). Exploring a two-population genetic algorithm. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2723, 1148–1159. https://doi.org/10.1007/3-540-45105-6_123
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