Summary
the 2014 International Symposium on Nonlinear Theory and its Applications
2014
Session Number:B1L-C
Session:
Number:B1L-C1
Solving Min-Max Multiple Traveling Salesman Problems by Chaotic Neural Network
Takafumi Matsuura, Kazumiti Numata,
pp.237-240
Publication Date:2014/9/14
Online ISSN:2188-5079
Summary:
In this paper, for solving min-max multiple traveling salesman problems (min-max mTSP), we propose two heuristic methods: a tabu search with CORSS-exchange and a chaotic search which controls execution of CROSS-exchange. In earlier studies, it has already been shown that the chaotic search shows better performances than the tabu search for NP-hard combinatorial optimization problems. However, it is not clear that the chaotic search is better than the tabu search for min-max type prob- lem. The simulation results for min-max mTSP show that the chaotic search exhibits also higher performance than the tabu search. In addition, the chaotic search shows better performances than the conventional methods: a team ant colony optimization algorithm and a method by using competition-based neural network.