Genetic heuristic for search space exploration

Authors:
Manuel Clergue;Philippe Collard
Affiliations:
I3S Laboratory, University of Nice-Sophia Antipolis, Sophia Antipolis, France;I3S Laboratory, University of Nice-Sophia Antipolis, Sophia Antipolis, France
Venue:
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Year:
1999

Citing 5
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Abstract

This paper deals with the way dual genetic algorithms (DGA), an extension of the standard ones, explore the search space. After a brief introduction presenting genetic algorithms and dualism, the fitness distance correlation is discussed in the context of dualism. From this discussion, a conjecture is made about the genetic: heuristic used by dual genetic algorithms to explore the search space. This conjecture is reinforced by the visualization of the population centroid trajectories in the plane fitness distance. These trajectories help to point out "leg-up" behaviors, which allow the dual genetic algorithm to reach the global optimum from walks on deceptive paths.