Solving TSP by using Lotka-Volterra neural networks

Authors:
Manli Li;Zhang Yi;Min Zhu
Affiliations:
Computational Intelligence Laboratory, School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 610054, PR China;Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, PR China;Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, PR China
Venue:
Neurocomputing
Year:
2009

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Abstract

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.