Genetic Drift in Sharing Methods

This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of the University of Illinois' products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE. For information on obtaining permission, send a blank e-mail message to [email protected]. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. Abstract| Adding a sharing method to a genetic algorithm promotes the formation and maintenance of stable subpopulations. This paper explores the limits of sharing by deriving closed-form expressions for the expected time to disappearance of a subpopula-tion. The time to disappearance is shown to be an exponential function of population size, with relative subpopulation tnesses determining the base of the exponential. However, disappearance time decreases rapidly as the number of subpopulations increases. Both theoretical and experimental illustrations are given of genetic drift in sharing.