Abstract
To find the global minimum of an NP-complete problem within a reasonable computational time is extremely difficult. The traveling salesman problem, in addition to being NP-complete, has a complicated solution set in terms of optimizing an energy function. A novel neural network that removes ambiguities in the solution set and eliminates local minima is described. This network obtains the global minimum at a small increase in computational time when compared to the Hopfield network. Salient features of this improved network are presented.
| Original language | English |
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| Pages | 552-555 |
| Number of pages | 4 |
| State | Published - 1989 |
| Externally published | Yes |
| Event | 4th IEEE Region 10th International Conference - TENCON '89 - Bombay, India Duration: 22 11 1989 → 24 11 1989 |
Conference
| Conference | 4th IEEE Region 10th International Conference - TENCON '89 |
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| City | Bombay, India |
| Period | 22/11/89 → 24/11/89 |