A novel coding method for genetic algorithms based on redundant binary numbers

  • Authors:

  • Akira Murayama;Akinori Kanasugi

  • Affiliations:

  • Graduate School of Engineering, Tokyo Denki University, Tokyo, Japan 101-8457;Graduate School of Engineering, Tokyo Denki University, Tokyo, Japan 101-8457

  • Venue:
  • Artificial Life and Robotics
  • Year:
  • 2010

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Abstract

This article proposes a novel genetic algorithm (GA) which switches the expression of the solution from a redundant binary number to a usual binary number. Furthermore, a GA which switches the expression from the Gray code to the usual binary number is proposed and compared. Comparisons of the performances among five GAs (binary number, redundant binary number, Gray code, switching from redundant binary number to binary number, switching from Gray code to binary number) are illustrated. The performances are evaluated by solving some equations. It is confirmed that the proposed GA effectively decreases the error rate.