Self-organization via competition, cooperation and categorization applied to extended vehicle routing problems

Yasuo Matsuyama*

*Corresponding author for this work

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

18 Citations (Scopus)

Abstract

Competitive learning in neural networks involving cooperation and categorization is discussed. Extended vehicle routing problems in the Euclidean space are discussed. A fixed number of vehicles with a shared depot make subtours around precategorized cities and collect demands. The minimal tour length and even loaded demands are conflicting requirements for the optimization. This situation does not appear in a simple traveling salesman problem. The self-organization method gives qualified approximate solutions without computational backtracks. Experiments were made on the USA532 set. All computations can be carried out by a conventional workstation.

Original languageEnglish
Title of host publicationProceedings. IJCNN-91-Seattle: International Joint Conference on Neural Networks
Editors Anon
Place of PublicationPiscataway, NJ, United States
PublisherPubl by IEEE
Pages385-390
Number of pages6
ISBN (Print)0780301641
Publication statusPublished - 1991
Externally publishedYes
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: 1991 Jul 81991 Jul 12

Other

OtherInternational Joint Conference on Neural Networks - IJCNN-91-Seattle
CitySeattle, WA, USA
Period91/7/891/7/12

ASJC Scopus subject areas

  • Engineering(all)

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