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 language | English |
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| Title of host publication | IJCNN. International Joint Conference on Neural Networks |
| Place of Publication | Piscataway, NJ, United States |
| Publisher | Publ by IEEE |
| Pages | 819-824 |
| Number of pages | 6 |
| Publication status | Published - 1990 |
| Externally published | Yes |
| Event | 1990 International Joint Conference on Neural Networks - IJCNN 90 Part 3 (of 3) - San Diego, CA, USA Duration: 1990 Jun 17 → 1990 Jun 21 |
Other
| Other | 1990 International Joint Conference on Neural Networks - IJCNN 90 Part 3 (of 3) |
|---|---|
| City | San Diego, CA, USA |
| Period | 90/6/17 → 90/6/21 |
ASJC Scopus subject areas
- Engineering(all)