DIGITAL PATTERN SEARCH AND ITS HYBRIDIZATION WITH GENETIC ALGORITHMS FOR GLOBAL OPTIMIZATION

Nam-Geun Kim, Youngsu Park, Sang Woo Kim

Abstract

In this paper, we present a new evolutionary algorithm called genetic pattern search algorithm (GPSA). The proposed algorithm is closely related to genetic algorithms (GAs) which use binary-coded genes. The main contribution of this paper is to propose a binary-coded pattern called digital pattern which is transformed from the real-coded pattern in general pattern search methods. In addition, we offer a self-adapting genetic algorithm by adopting a digital pattern that modifies the step size and encoding resolution of previous optimization procedures, and chases the optimal pattern’s direction. Finally, we compare GPSA with GA in the robustness and performance of optimization. All experiments employ the well-known benchmark functions whose functional values and coordinates of each global minimum have already been reported.

References

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  17. 10-1 10-1 0.5 1.0 1.5 2.0 2.5 3.0 Number of function evaluations 3.5 4.0
  18. x1e4
  19. -2000.0 0.5 1.0 1.5 2.0 2.5 3.0 Number of function evaluations 3.5 4.0
  20. x1e4 1 2 3
  21. Number of function evaluations 4 x1e4 1 2 3
  22. Number of function evaluations 4
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Paper Citation


in Harvard Style

Kim N., Park Y. and Woo Kim S. (2007). DIGITAL PATTERN SEARCH AND ITS HYBRIDIZATION WITH GENETIC ALGORITHMS FOR GLOBAL OPTIMIZATION . In Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-972-8865-82-5, pages 380-387. DOI: 10.5220/0001650903800387


in Bibtex Style

@conference{icinco07,
author={Nam-Geun Kim and Youngsu Park and Sang Woo Kim},
title={DIGITAL PATTERN SEARCH AND ITS HYBRIDIZATION WITH GENETIC ALGORITHMS FOR GLOBAL OPTIMIZATION},
booktitle={Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},
year={2007},
pages={380-387},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001650903800387},
isbn={978-972-8865-82-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the Fourth International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - DIGITAL PATTERN SEARCH AND ITS HYBRIDIZATION WITH GENETIC ALGORITHMS FOR GLOBAL OPTIMIZATION
SN - 978-972-8865-82-5
AU - Kim N.
AU - Park Y.
AU - Woo Kim S.
PY - 2007
SP - 380
EP - 387
DO - 10.5220/0001650903800387