On properties of genetic operators from a network analytical viewpoint

Authors:
Hiroyuki Funaya;Kazushi Ikeda
Affiliations:
Department of Systems, Kyoto University, Kyoto, Japan;Department of Systems, Kyoto University, Kyoto, Japan
Venue:
ICONIP'06 Proceedings of the 13th international conference on Neural information processing - Volume Part III
Year:
2006

Citing 4
Cited 0

Small worlds: the dynamics of networks between order and randomness

Small worlds: the dynamics of networks between order and randomness
Genetic Algorithms in Search, Optimization and Machine Learning

Genetic Algorithms in Search, Optimization and Machine Learning
The Estimation of Distributions and the Minimum Relative Entropy Principle

Evolutionary Computation
A further result on the Markov chain model of genetic algorithms and its application to a simulated annealing-like strategy

IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics

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Abstract

In recent years, network analysis has revealed that some real networks have the properties of small-world and/or scale-free networks. In this paper, a simple Genetic Algorithm (GA) is regarded as a network where each node and each edge respectively represent a population and the possibility of the transition between two nodes. The characteristic path length, which is one of the most popular criterion in small-world networks, is derived analytically. The results show how the crossover operation works in GAs to shorten the path length between two populations, compared to the length of the network with the mutation operation.