Adaptive evolutionary optimization algorithm based on partitioning method

Chang-Wook Han; Seong-Hyun Jeong; Ulugbek R. Umirov; Jung-Il Park

doi:10.14864/softscis.2006.0.1695.0

SCIS & ISIS 2006

Session ID : SA-D2-1

DOI https://doi.org/10.14864/softscis.2006.0.1695.0

Conference information

Host: Japan SOciety for Fuzzy Theory and intelligent informatics

Co-host: The Korea Fuzzy Logic and Intelligent Systems Society, IEEE Computational Intelligence Society, The International Fuzzy Systems Association, 21th Century COE Program "Creation of Agent-Based Social Systems Sciences"

SA-D2 Theoretical and Practical Perspective of Computational Intelligence

Adaptive evolutionary optimization algorithm based on partitioning method

*Chang-Wook Han, Seong-Hyun Jeong, Ulugbek R. Umirov, Jung-Il Park

Author information

Keywords: genetic algorithm, evolutionary computation, adaptive partitioning

CONFERENCE PROCEEDINGS FREE ACCESS

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Abstract

This paper proposes an adaptive genetic algorithm based on partitioning method. The partitioning method, which enables a genetic algorithm to find a solution very effectively, adaptively divides the search space into promising sub-spaces to reduce the complexity of optimization. This partitioning method is more effective as the complexity of the search space is increasing. The validity of the proposed method is conformed by applying it to several bench mark test function examples and a traveling salesman problem.

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