IEICE TRANSACTIONS on Information
An Empirical Performance Comparison of Niching Methods for Genetic Algorithms
Summary :
Various niching methods have been developed to maintain the population diversity. The feature of these methods is to prevent the proliferation of similar individuals in the niche (subpopulation) based on the similarity measure. This paper demonstrates that they are effective to avoid premature convergence in a case where only one global optimum in multimodal functions is searched. The performance of major niching methods in such a case is investigated and compared by experiments using seven benchmark functions. The niching methods tested in this paper are deterministic crowding, probabilistic crowding, restricted tournament selection, clearing procedure and diversity-control-oriented genetic algorithm (DCGA). According to the experiment, each method shows a fairly good global-optimum-searching capability. However, no method can completely avoid premature convergence in all functions. In addition, no method shows a better searching capability than the other methods in all functions.
- Publication
- IEICE TRANSACTIONS on Information Vol.E85-D No.11 pp.1872-1880
- Publication Date
- 2002/11/01
- Publicized
- Online ISSN
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- Type of Manuscript
- PAPER
- Category
- Biocybernetics, Neurocomputing
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Hisashi SHIMODAIRA, "An Empirical Performance Comparison of Niching Methods for Genetic Algorithms" in IEICE TRANSACTIONS on Information,
vol. E85-D, no. 11, pp. 1872-1880, November 2002, doi: .
Abstract: Various niching methods have been developed to maintain the population diversity. The feature of these methods is to prevent the proliferation of similar individuals in the niche (subpopulation) based on the similarity measure. This paper demonstrates that they are effective to avoid premature convergence in a case where only one global optimum in multimodal functions is searched. The performance of major niching methods in such a case is investigated and compared by experiments using seven benchmark functions. The niching methods tested in this paper are deterministic crowding, probabilistic crowding, restricted tournament selection, clearing procedure and diversity-control-oriented genetic algorithm (DCGA). According to the experiment, each method shows a fairly good global-optimum-searching capability. However, no method can completely avoid premature convergence in all functions. In addition, no method shows a better searching capability than the other methods in all functions.
URL: https://global.ieice.org/en_transactions/information/10.1587/e85-d_11_1872/_p
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@ARTICLE{e85-d_11_1872,
author={Hisashi SHIMODAIRA, },
journal={IEICE TRANSACTIONS on Information},
title={An Empirical Performance Comparison of Niching Methods for Genetic Algorithms},
year={2002},
volume={E85-D},
number={11},
pages={1872-1880},
abstract={Various niching methods have been developed to maintain the population diversity. The feature of these methods is to prevent the proliferation of similar individuals in the niche (subpopulation) based on the similarity measure. This paper demonstrates that they are effective to avoid premature convergence in a case where only one global optimum in multimodal functions is searched. The performance of major niching methods in such a case is investigated and compared by experiments using seven benchmark functions. The niching methods tested in this paper are deterministic crowding, probabilistic crowding, restricted tournament selection, clearing procedure and diversity-control-oriented genetic algorithm (DCGA). According to the experiment, each method shows a fairly good global-optimum-searching capability. However, no method can completely avoid premature convergence in all functions. In addition, no method shows a better searching capability than the other methods in all functions.},
keywords={},
doi={},
ISSN={},
month={November},}
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TY - JOUR
TI - An Empirical Performance Comparison of Niching Methods for Genetic Algorithms
T2 - IEICE TRANSACTIONS on Information
SP - 1872
EP - 1880
AU - Hisashi SHIMODAIRA
PY - 2002
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E85-D
IS - 11
JA - IEICE TRANSACTIONS on Information
Y1 - November 2002
AB - Various niching methods have been developed to maintain the population diversity. The feature of these methods is to prevent the proliferation of similar individuals in the niche (subpopulation) based on the similarity measure. This paper demonstrates that they are effective to avoid premature convergence in a case where only one global optimum in multimodal functions is searched. The performance of major niching methods in such a case is investigated and compared by experiments using seven benchmark functions. The niching methods tested in this paper are deterministic crowding, probabilistic crowding, restricted tournament selection, clearing procedure and diversity-control-oriented genetic algorithm (DCGA). According to the experiment, each method shows a fairly good global-optimum-searching capability. However, no method can completely avoid premature convergence in all functions. In addition, no method shows a better searching capability than the other methods in all functions.
ER -
English
