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Genetic algorithm with dynamic variable number of individuals and accuracy

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Abstract

This paper proposes a novel processor for genetic algorithm (GA) that can dynamically change number of individuals and accuracy. In conventional GA, number of population and accuracy are fixed. However, the accuracy of solution is low at first-half stage. Therefore, the number of population is doubled at expense of the accuracy of solution, and the searching ability is improved at first-stage in the proposed GA processor. Then, the number of population is reduced by half, and the accuracy is improved at second-half stage. As a result, the searching ability is improved. The proposed GA processor was designed and verified. The effectiveness of proposed method was confirmed by applying to the knapsack problem.

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Authors and Affiliations

  1. Graduate School of Engineering, Tokyo Denki University, 2-2 Kanda-Nishiki-Cho, Chiyoda-ku, Tokyo, 101-8457, Japan

    Akihiko Tsukahara & Akinori Kanasugi

Authors
  1. Akihiko Tsukahara
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  2. Akinori Kanasugi
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Corresponding author

Correspondence to Akinori Kanasugi.

Additional information

Recommended by Guest Editor Phill Kyu Rhee. This work was supported by the grant from Research Institute for Science and Technology, Tokyo Denki University (Q06J-03).

Akihiko Tsukahara received the B.E. degree in Electronic Engineering from Tokyo Denki University in 2005. He is currently a M.E. student in Tokyo Denki University. His research interests include VLSI design for genetic algorithm and rough sets.

Akinori Kanasugi received the B.E., M.E. and Ph.D. degrees from Saitama University, Japan, in 1983, 1985 and 1994, respectively. After a research associate in Saitama University, he moved to Tokyo Denki University in 2002, where he is currently a Professor in the Faculty of Engineering. His current research interests are in the development of VLSI systems such as reconfigurable processor, GA processor, and rough sets processor.

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Tsukahara, A., Kanasugi, A. Genetic algorithm with dynamic variable number of individuals and accuracy. Int. J. Control Autom. Syst. 7, 1–6 (2009). https://doi.org/10.1007/s12555-009-0101-3

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  • DOI: https://doi.org/10.1007/s12555-009-0101-3

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