Presentation | 2014-07-21 Solving Ability of Lin-Kernighan Method Driven by Chaotic Dynamics for Traveling Salesman Problems Takahiro MITSUOKA, Mikio HASEGAWA, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Effectiveness of chaos for optimization has been shown by many previous researches. In this paper, a chaotic search based on the 2-opt for the Traveling Salesman Problem (TSP) is extended to the k-opt based version. A chaotic search based on the adaptive k-opt, whose k is adaptively changed in similar way to the Lin-Kernighan method, is proposed. Our proposed method is based on the tabu search. First, a conventional tabu search is implemented on a neural network model, which has refractory effects on each neuron. The tabu search neural network can be simply extended to chaotic neural network, by replacing the output function with analog sigmoidal function. By numerical simulations, it is shown that the proposed method solves good near optimum solutions, which is about 1% different from the best known solutions, with only 5000 iterations even for an 11849-city TSP. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Chaos / Combinatorial Optimization / Neural Networks / Lin-Kernighan Method / Tabu Search |
Paper # | NLP2014-35 |
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Committee | NLP |
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Conference Date | 2014/7/14(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Solving Ability of Lin-Kernighan Method Driven by Chaotic Dynamics for Traveling Salesman Problems |
Sub Title (in English) | |
Keyword(1) | Chaos |
Keyword(2) | Combinatorial Optimization |
Keyword(3) | Neural Networks |
Keyword(4) | Lin-Kernighan Method |
Keyword(5) | Tabu Search |
1st Author's Name | Takahiro MITSUOKA |
1st Author's Affiliation | Faculty of Engineering, Tokyo University of Science() |
2nd Author's Name | Mikio HASEGAWA |
2nd Author's Affiliation | Faculty of Engineering, Tokyo University of Science |
Date | 2014-07-21 |
Paper # | NLP2014-35 |
Volume (vol) | vol.114 |
Number (no) | 145 |
Page | pp.pp.- |
#Pages | 4 |
Date of Issue |