The Spatially-Dispersed Genetic Algorithm

Abstract. Spatially structured population models improve the performance of genetic algorithms by assisting the selection scheme in maintaining diversity. A significant concern with these systems is that they need to be carefully configured in order to operate at their optimum. Failure to do so can often result in performance that is significantly under that of an equivalent non-spatial implementation. This paper introduces a GA that uses a population structure that requires no additional configuration. Early experimentation with this paradigm indicates that it is able to improve the searching abilities of the genetic algorithm on some problem domains. 1 The Spatially-Dispersed Genetic Algorithm The spatially-dispersed genetic algorithm (sdGA) is an alternative method of incorporating population genetics models into genetic algorithms by using a two dimensional Euclidean space to hold the members of the population [1]. This space is infinite and continuous. The placing of individu...

• Type: Conference
• Year: 2003
• Where: GECCO
• Authors: Grant Dick
• Keywords: GECCO 2003, Genetic Algorithms, Population Models, Spatially-dispersed Genetic Algorithm