Exploring a two-population genetic algorithm

Authors:
Steven Orla Kimbrough;Ming Lu;David Harlan Wood;D. J. Wu
Affiliations:
University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA;University of Delaware, CIS Dept., Newark, DE;DuPree College of Management, Georgia Institute of Technology, Atlanta, GA
Venue:
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Year:
2003

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Abstract

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.