The Role of Mate Selection in Genetic Algorithms
The process of information exchange among the population of
individuals manipulated by Genetic Algorithms (GAs) involves two
key components: crossover and mate selection. The central theme of
my thesis concentrates on the investigation of effects of "mate
selection" in GAs. The prevalence of mate selection in biology is
widely recognized, yet a systematic investigation of this subject
in GA research is still lacking. The goal of my work is to propose
a framework that facilitates exploration of this direction.
In this talk, I'll present motivations for this work, and describe
investigations of the basic properties of mate selection in the
context of GA. Then I'll discuss my study based on two classes of
more complicated, building-block-based problems---the Royal Road
functions and the hyperplane-defined functions. With the results
obtained, I introduce an important hypothesis regarding the role
of mate selection in GAs. That is, if one's goal is to improve the
GA's search for best-so-far solutions, then on easy problems a
dissimilarity-based mate selection scheme is more beneficial. If
problems present sufficient difficulty, the GA's search power can
be further improved by reducing the selection pressure toward
higher-fitness individuals while selecting mates.
I'll discuss how this hypothesis is validated based on several
more realistic, non-building-block-based benchmark testbeds. The
encouraging results imply that the ideas of mate selection
proposed can be applied to practical problems. I will also discuss
a more general setting in the context of multimodal function
optimization, where identifying multiple peaks and maintaining
subpopulations of the search space are two central themes. An
immune system model is employed to study these two problems. The
experimental results indeed shed more light on how mate selection
schemes compare to traditional selection schemes. Finally, I'll
discuss how mate selection can fit in the framework of contextual
genetic algorithms.
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