2002年3月
Doubly constrained network for combinatorial optimization
NEUROCOMPUTING
- ,
- 巻
- 43
- 号
- 開始ページ
- 239
- 終了ページ
- 257
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.1016/S0925-2312(01)00343-5
- 出版者・発行元
- ELSEVIER SCIENCE BV
In this paper, we propose a neural approach for solving combinatorial optimization problems having two competing sets of constraints. Based on the Lagrange multiplier method, a discrete-time dynamical system is designed so that those constraints are automatically satisfied. We study the convergence and the bifurcation properties. We also show experimental results when applied to traveling salesman problems and quadratic assignment problems. Our approach can obtain better solutions even for relatively large-scale problems than binary or Potts spin approaches. (C) 2002 Elsevier Science B.V. All rights reserved.
- リンク情報
- ID情報
-
- DOI : 10.1016/S0925-2312(01)00343-5
- ISSN : 0925-2312
- Web of Science ID : WOS:000173203200015