A preliminary study of crowding with biased crossover

Authors:
Shigeyoshi Tsutsui;Noriyuki Fujimoto
Affiliations:
Hannan University, Matsubara, Osaka, Japan;Osaka Prefecture University, Sakai, Osaka, Japan
Venue:
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Year:
2013

Citing 6
Cited 0

Genetic algorithms with sharing for multimodal function optimization

Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Niching methods for genetic algorithms

Niching methods for genetic algorithms
An analysis of the behavior of a class of genetic adaptive systems.

An analysis of the behavior of a class of genetic adaptive systems.
The crowding approach to niching in genetic algorithms

Evolutionary Computation
Generalized crowding for genetic algorithms

Proceedings of the 12th annual conference on Genetic and evolutionary computation
cAS: ant colony optimization with cunning ants

PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper proposes a novel crowding method, which is called "Crowding with Biased Crossover (CBX)". The Biased crossover operator begins with two parents. Then two offspring individuals are created, each offspring taking more characteristics from one of the two parents. This is an easy method to perform replacement between parents and offspring individuals. Experimental results showed that CBX is very effective in finding both single global solutions and multiple solutions (niching).