A kind of genetic algorithm based on compound mutation strategy and performance study

  • Authors:

  • Fachao Li;Tingyu Zhang;Chenxia Jin

  • Affiliations:

  • School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang, China;School of Science, Hebei University of Science and Technology, Shijiazhuang, China;School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang, China

  • Venue:
  • WiCOM'09 Proceedings of the 5th International Conference on Wireless communications, networking and mobile computing
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Genetic algorithm (GA), as a kind of important intelligence computing tool, is a wide research content in the academic circle and the application domain now. In this paper, for the mutation operation of GA, by combining with the essential feature, from structural and visualized angle, we implement different mutation strategy to individual of different fitness value in every generation, and establish a genetic algorithm based on compound mutation (denoted by BCM-GA, for short). Further, we discuss the global convergence of BCM-GA by using the Markov chain theory, and analyze the performance of BCM-GA through an example. All the results indicate that, BCM-GA is obviously higher than real number code genetic algorithm (denoted by B10GA, for short) in the convergence time and convergence precision.