抄録
In this article, we propose a new elastic net method to solve the traveling salesman problem by introducing some time-dependent parameters. This method can help network neurons move quickly near to the cities at early stage, and gradually increase the strength that pulls neurons towards their neighbours on the path to minimize the total path length. This enables the network to have superior ability of searching for cities, and converge sooner to a saturated state. Simulation results illustrate that the proposed network performs better than the classical elastic net for optimization both in solution quality and convergence speed.
| 本文言語 | 英語 |
|---|---|
| ページ（範囲） | 1329-1335 |
| ページ数 | 7 |
| ジャーナル | Neurocomputing |
| 巻 | 72 |
| 号 | 4-6 |
| DOI | |
| 出版ステータス | 出版済み - 2009/01 |
ASJC Scopus 主題領域
- コンピュータ サイエンスの応用
- 認知神経科学
- 人工知能