New topologies for genetic search space
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Adjusting population distance for the dual-population genetic algorithm
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
A dual-population genetic algorithm for adaptive diversity control
IEEE Transactions on Evolutionary Computation
Ectropy of diversity measures for populations in Euclidean space
Information Sciences: an International Journal
Operator-Based distance for genetic programming: subtree crossover distance
EuroGP'05 Proceedings of the 8th European conference on Genetic Programming
Analysing the effects of diverse operators in a genetic programming system
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part I
Exploration and exploitation in evolutionary algorithms: A survey
ACM Computing Surveys (CSUR)
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Gene space, as it is currently formulated, cannot provide a solid basis for investigating the behavior of the GA. We instead propose an approach that takes population effects into account. Starting from a discussion of diversity, we develop a distance measure between populations and thereby a population metric space. We finally argue that one specific parameterization of this measure is particularly appropriate for use with GAs.