On the choice of the offspring population size in evolutionary algorithms

T Jansen, KAD Jong, I Wegener - Evolutionary Computation, 2005 - direct.mit.edu
T Jansen, KAD Jong, I Wegener
Evolutionary Computation, 2005direct.mit.edu
Evolutionary algorithms (EAs) generally come with a large number of parameters that have
to be set before the algorithm can be used. Finding appropriate settings is a diffi-cult task.
The influence of these parameters on the efficiency of the search performed by an
evolutionary algorithm can be very high. But there is still a lack of theoretically justified
guidelines to help the practitioner find good values for these parameters. One such
parameter is the offspring population size. Using a simplified but still realistic evolutionary …
Abstract
Evolutionary algorithms (EAs) generally come with a large number of parameters that have to be set before the algorithm can be used. Finding appropriate settings is a diffi- cult task. The influence of these parameters on the efficiency of the search performed by an evolutionary algorithm can be very high. But there is still a lack of theoretically justified guidelines to help the practitioner find good values for these parameters. One such parameter is the offspring population size. Using a simplified but still realistic evolutionary algorithm, a thorough analysis of the effects of the offspring population size is presented. The result is a much better understanding of the role of offspring population size in an EA and suggests a simple way to dynamically adapt this parameter when necessary.
MIT Press
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