A hybrid strategy: Real-coded genetic algorithm and chaotic search

Chun Kai Zhang; Hui He Shao

A hybrid strategy: Real-coded genetic algorithm and chaotic search

Chun Kai Zhang^*
, Hui He Shao

^*Corresponding author for this work

Shanghai Jiao Tong University

Research output: Contribution to journal › Conference article › peer-review

12 Scopus citations

Abstract

A new real-coded GAs is proposed which utilizes chaotic search and variable evolutionary rate. By introducing them, this algorithm can better simulate the process of biologic evolution, and possess the better hill-climbing ability. And "family competition" is added into the process of mutation and the operating order of mutation and crossover operators is adaptively changed in the different evolutionary stage. Compared with the self-adaptive GAs, it can overcome the shortcoming of premature convergence and stagnation, and effectively solves the problem of global convergence.

Original language	English
Pages (from-to)	2361-2364
Number of pages	4
Journal	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics
Volume	4
State	Published - 2001
Externally published	Yes
Event	2001 IEEE International Conference on Systems, Man and Cybernetics - Tucson, AZ, United States Duration: 7 Oct 2001 → 10 Oct 2001

Keywords

Chaotic search
Hill-climbing ability
Real-coded GAs

Cite this

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title = "A hybrid strategy: Real-coded genetic algorithm and chaotic search",

abstract = "A new real-coded GAs is proposed which utilizes chaotic search and variable evolutionary rate. By introducing them, this algorithm can better simulate the process of biologic evolution, and possess the better hill-climbing ability. And {"}family competition{"} is added into the process of mutation and the operating order of mutation and crossover operators is adaptively changed in the different evolutionary stage. Compared with the self-adaptive GAs, it can overcome the shortcoming of premature convergence and stagnation, and effectively solves the problem of global convergence.",

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AB - A new real-coded GAs is proposed which utilizes chaotic search and variable evolutionary rate. By introducing them, this algorithm can better simulate the process of biologic evolution, and possess the better hill-climbing ability. And "family competition" is added into the process of mutation and the operating order of mutation and crossover operators is adaptively changed in the different evolutionary stage. Compared with the self-adaptive GAs, it can overcome the shortcoming of premature convergence and stagnation, and effectively solves the problem of global convergence.

KW - Chaotic search

KW - Hill-climbing ability

KW - Real-coded GAs

UR - https://www.scopus.com/pages/publications/0035721431

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AN - SCOPUS:0035721431

SN - 0884-3627

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JO - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

JF - Proceedings of the IEEE International Conference on Systems, Man and Cybernetics

Y2 - 7 October 2001 through 10 October 2001

ER -

A hybrid strategy: Real-coded genetic algorithm and chaotic search

Abstract

Keywords

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