Competitive self-organization and combinatorial optimization: Applications to traveling salesman problem

Yasuo Matsuyama

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

The author discusses algorithms of competitive self-organization and their application to a typical combinatorial problem, the traveling salesman problem. The main feature of the proposed algorithm is the sophisticated use of excitatory/inhibitory intralayer connections of neurons combined with a judicious selection of neural network topology. Such properties contribute to obtaining excellent approximate solutions. Five hundred sets of 30-city solutions are compared with those obtained by a pure simulated annealing method. From this comparison, it is found that a considerable number of the solutions obtained by this self-organization method are highly likely to be the optimal tours. Successive training algorithms are mainly used; however, applications of batch training algorithms are also discussed. Implications for multisalesman problems are discussed.

Original languageEnglish
Title of host publicationIJCNN. International Joint Conference on Neural Networks
Place of PublicationPiscataway, NJ, United States
PublisherPubl by IEEE
Pages819-824
Number of pages6
Publication statusPublished - 1990
Externally publishedYes
Event1990 International Joint Conference on Neural Networks - IJCNN 90 Part 3 (of 3) - San Diego, CA, USA
Duration: 1990 Jun 171990 Jun 21

Other

Other1990 International Joint Conference on Neural Networks - IJCNN 90 Part 3 (of 3)
CitySan Diego, CA, USA
Period90/6/1790/6/21

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ASJC Scopus subject areas

  • Engineering(all)

Cite this

Matsuyama, Y. (1990). Competitive self-organization and combinatorial optimization: Applications to traveling salesman problem. In IJCNN. International Joint Conference on Neural Networks (pp. 819-824). Publ by IEEE.