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Research Paper #789

Title:Co-Evolution of Operator Settings in Genetic Algorithms
Authors:Tuson,AL; Ross,PM
Date:Jan 1996
Presented:Submitted to the 1996 AISB Workshop on Evolutionary Computing
Abstract:Typical genetic algorithm implementations use operator settings that are fixed throughout a given run. Varying these settings is known to improve performance - the problem is knowing how to vary them. One approach is to encode the operator settings into each member of the GA population, and allow them to evolve. This paper describes an empirical investigation into the effect of co-evolving operator settings, for some common problems in the genetic algorithms field. The results obtained indicate that the problem representation, and the choice of operators on the encoded operator settings are important for useful adaptation.

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