Genetic algorithms, efficiency enhancement, and deciding well with fitness functions with differing variances
24 June 2002Sastry, K., Goldberg, D. E. (2002). Proceedings of the Genetic and Evolutionary Computation Conference. 528—535. [Full paper - PDF] [Full paper - PS] [Presentation slides].
Abstract:
This study investigates the decision making between fitness function with differing variance and computational-cost values. The objective of this decision making is to provide evaluation relaxation and thus enhance the efficiency of the genetic search. A decision-making strategy has been developed to maximize speed-up using facetwise models for the convergence time and population sizing. Results indicate that using this decision making, significant speed-up can be obtained.
Posted in Conference Proceedings, Genetic and Evolutionary Algorithm Theory, Principled Efficiency Enhancement Techniques, Publications |
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