Chaotic Neurodynamical search with small number of neurons for solving QAP

DOI Web Site 被引用文献2件 参考文献7件
  • Ohnishi Hikaru
    Department of Management Science, Graduate School of Engineering, Tokyo University of Science
  • Shimada Yutaka
    Department of Management Science, Graduate School of Engineering, Tokyo University of Science Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science
  • Fujiwara Kantaro
    Department of Management Science, Graduate School of Engineering, Tokyo University of Science Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science
  • Ikeguchi Tohru
    Department of Management Science, Graduate School of Engineering, Tokyo University of Science Department of Information and Computer Technology, Faculty of Engineering, Tokyo University of Science

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Quadratic Assignment Problem (QAP) is one of the combinatorial optimization problems which are classified into Nondeterministic Polynomial time solvable (NP)-hard problems. Therefore, it is important to develop algorithms for finding good approximate solutions in short time. In this paper, we proposed an algorithm for approximately solving QAP by using chaotic neurodynamics. The proposed algorithm has three characteristics. First, compared with the conventional method, the number of neurons was substantially reduced. Second, the effect of external inputs to neurons was changed. Third, a new parameter tuning method was introduced. As a result, our algorithm can find good solutions compared with the conventional method using chaotic neurodynamics.

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