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A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes

Srinivasa, KG and Srichand, P and Bhat, Anuj and Venugopal, KR and Patnaik, LM (2007) A genetic algorithm with characteristic amplification through multiple geographically isolated populations and varied fitness landscapes. In: 15th International Conference on Advanced Computing and Communications, DEC 18-21, 2007, Guwahati, Assam, India.

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Abstract

This paper proposes a new approach, wherein multiple populations are evolved on different landscapes. The problem statement is broken down, to describe discrete characteristics. Each landscape, described by its fitness landscape is used to optimize or amplify a certain characteristic or set of characteristics. Individuals from each of these populations are kept geographically isolated from each other Each population is evolved individually. After a predetermined number of evolutions, the system of populations is analysed against a normalized fitness function. Depending on this score and a predefined merging scheme, the populations are merged, one at a time, while continuing evolution. Merging continues until only one final population remains. This population is then evolved, following which the resulting population will contain the optimal solution. The final resulting population will contain individuals which have been optimized against all characteristics as desired by the problem statement. Each individual population is optimized for a local maxima. Thus when populations are merged, the effect is to produce a new population which is closer to the global maxima.

Item Type: Conference Paper
Publisher: IEEE
Additional Information: Copyright 2007 IEEE. 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 to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Biological Sciences > Microbiology & Cell Biology
Date Deposited: 09 Jun 2010 04:38
Last Modified: 19 Sep 2010 06:00
URI: http://eprints.iisc.ac.in/id/eprint/27167

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