Adaptive evolutionary genetic algorithms on a class of combinatorial optimization problems

Sheng Zhong*, Baihai Zhang, Qiao Li, Jun Li, Zhiwei Lin

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper investigates an adaptive evolutionary genetic algorithm on combinatorial optimization problem, where the solution space can be organized inform of a subset tree. A kind of genetic gene uniform encode scheme and adaptive evolution idea are used before proceeding crossover operation, and crossover is achieved between the current and previous generations individual. The orthogonal table approach is utilized to produce initial population, which can satisfy the multiplicity of the initial population. Two examples are provided to illustrate the effectiveness of the proposed methods.

Original languageEnglish
Title of host publicationProceedings - 4th International Conference on Natural Computation, ICNC 2008
Pages166-170
Number of pages5
DOIs
Publication statusPublished - 2008
Event4th International Conference on Natural Computation, ICNC 2008 - Jinan, China
Duration: 18 Oct 200820 Oct 2008

Publication series

NameProceedings - 4th International Conference on Natural Computation, ICNC 2008
Volume1

Conference

Conference4th International Conference on Natural Computation, ICNC 2008
Country/TerritoryChina
CityJinan
Period18/10/0820/10/08

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