Niche identification techniques in multimodal genetic search with sharing scheme

  • Authors:

  • Chyi-Yeu Lin;Wen-Hong Wu

  • Affiliations:

  • Department of Mechanical Engineering, National Taiwan University of Science and Technology, 43 Keelung Road, Section 4, Taipei 10672, Taiwan, ROC;Department of Mechanical Engineering, National Taiwan University of Science and Technology, 43 Keelung Road, Section 4, Taipei 10672, Taiwan, ROC

  • Venue:
  • Advances in Engineering Software
  • Year:
  • 2002

Quantified Score

Hi-index 0.00

Visualization

Abstract

Genetic algorithms with sharing have been applied in many multimodal optimization problems with success. Traditional sharing schemes require the definition of a common sharing radius, but the predefined radius cannot fit most problems where design niches are of different sizes. Yin and Germay proposed a sharing scheme with cluster analysis methods, which can determine design clusters of different sizes. Since clusters are not necessarily coincident with niches, sharing with clustering techniques fails to provide maximum sharing effects. In this paper, a sharing scheme based on niche identification techniques (NIT) is proposed, which is capable of determining the center location and radius of each of existing niches based on fitness topographical information of designs in the population. Genetic algorithms with NIT were tested and compared to GAs with traditional sharing scheme and sharing with cluster analysis methods in four illustrative problems. Results of numerical experiments showed that the sharing scheme with NIT improved both search stability and effectiveness of locating multiple optima. The niche-based genetic algorithm and the multiple local search approach are compared in the fifth illustrative problem involving a discrete ten-variable bump function problem.