K$\bigoplus$1 Composite Genetic Algorithm and Its Properties

  • Authors:

  • Fachao Li;Limin Liu

  • Affiliations:

  • College of Economics and Management, Hebei University of Science and Technology, Shijiazhuang Hebei 050018, China and College of Science, Hebei University of science and technology, Shijiazhuang H ...;College of Science, Hebei University of science and technology, Shijiazhuang Hebei 050018, China

  • Venue:
  • ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
  • Year:
  • 2009

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Abstract

In view of the slowness and the locality of convergence for Simple Genetic Algorithm (SGA for short) in solving complex optimization problems, K$\bigoplus$1 Composite Genetic Algorithm (K$\bigoplus$1-CGA for short), as an improved genetic algorithm, is proposed by reducing the optimization-search range gradually, the structure and the implementation steps of K$\bigoplus$1-CGA are also given; then consider its global convergence under the elitist preserving strategy using Markov chain theory, and analyze its performance from different aspects through simulation. All these indicate that the new algorithm possesses interesting advantages such as better convergence, less chance trapping into premature states. So it can be widely used in many optimization problems with large-scale and high- accuracy.