Non-linear integer programming based on particle swarm optimisation combining diversification and intensification

  • Authors:

  • Takeshi Matsui;Masatoshi Sakawa;Kosuke Kato;Koichi Matsumoto

  • Affiliations:

  • Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan.;Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan.;Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan.;Department of Artificial Complex Systems Engineering, Graduate School of Engineering, Hiroshima University, 1-4-1, Kagamiyama, Higashi-Hiroshima, 739-8527, Japan

  • Venue:
  • International Journal of Knowledge Engineering and Soft Data Paradigms
  • Year:
  • 2010

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Abstract

In this paper, focusing on non-linear integer programming problems, we propose an approximate solution method based on particle swarm optimisation (PSO) proposed by Kennedy et al. And we developed a new PSO method which is applicable to discrete optimisation problems by incorporating a new method for generating initial search points, the rounding of values obtained by the move scheme and the revision of move methods. Furthermore, we showed the efficiency of the proposed PSO method by comparing it with an existing method through the application of them into the numerical examples. Moreover we expanded revised PSO method for application to non-linear integer programming problems and showed more efficiency than genetic algorithm. However, variance of the solutions obtained by the PSO method is large and accuracy is not so high. Thus, we consider improvement of accuracy introducing diversification and intensification.