Solving TSP by using Lotka-Volterra neural networks

被引：11
|
作者：
Li, Manli [1 ]
Yi, Zhang [2 ]
Zhu, Min [2 ]
机构：
[1] Univ Elect Sci & Technol China, Computat Intelligence Lab, Sch Engn & Comp Sci, Chengdu 610054, Peoples R China
[2] Sichuan Univ, Coll Comp Sci, Machine Intelligence Lab, Chengdu 610065, Peoples R China
来源：
NEUROCOMPUTING | 2009年 / 72卷 / 16-18期
关键词：
Neural networks; Lotka-Volterra neural networks; Traveling salesman problem; STABILITY CONDITIONS; FEATURE BINDING; LOCAL MINIMA; MODEL;
D O I：
10.1016/j.neucom.2009.05.002
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper proposes a new approach to solve traveling salesman problem (TSP) by using a class of Lotka-Volterra neural networks (LVNN) with global inhibition. Some stability criteria that ensure the convergence of valid solutions are obtained. It is proved that an equilibrium state is stable if and only if it corresponds to a valid solution of the TSP. Thus, a valid solution can always be obtained whenever the network convergence to a stable state. A set of analytical conditions for optimal settings of LVNN is derived. Simulation results illustrate the theoretical analysis. (C) 2009 Elsevier B.V. All rights reserved.
引用
收藏
页码：3873 / 3880
页数：8
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