Presentation | 2009-11-11 Solving Traveling Salesman Problem Using 2-opt and Or-opt Algorithms Driven by Chaotic Neurons Takafumi MATSUURA, Tohru IKEGUCHI, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | To find near optimum solutions of TSPs, a method with chaotic neurodynamics for solving TSPs has already been proposed. To avoid local minima, in the method, 2-opt algorithm and Or-opt algorithm for solving TSP are driven by chaotic neurodynamics. In the method, two local searches are driven by the same chaotic neuron. As a result, this method shows good performance, even though the 2-opt and the Or-opt algorithms are simple local search. In this report, to improve the performance of this method, we propose a new method. In the proposed method, the 2-opt and Or-opt algorithms are driven by different chaotic neurons. As a result, the proposed method shows higher performance than the previous chaotic search methods. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Traveling Salesman Problem / Chaotic Neural Network / 2-opt algorithm / Or-opt algorithm |
Paper # | NLP2009-93 |
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Conference Information | |
Committee | NLP |
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Conference Date | 2009/11/4(1days) |
Place (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Nonlinear Problems (NLP) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Solving Traveling Salesman Problem Using 2-opt and Or-opt Algorithms Driven by Chaotic Neurons |
Sub Title (in English) | |
Keyword(1) | Traveling Salesman Problem |
Keyword(2) | Chaotic Neural Network |
Keyword(3) | 2-opt algorithm |
Keyword(4) | Or-opt algorithm |
1st Author's Name | Takafumi MATSUURA |
1st Author's Affiliation | Graduate School of Science and Engineering, Saitama University() |
2nd Author's Name | Tohru IKEGUCHI |
2nd Author's Affiliation | Graduate School of Science and Engineering, Saitama University:Saitama Uneversity Brain Science Institute |
Date | 2009-11-11 |
Paper # | NLP2009-93 |
Volume (vol) | vol.109 |
Number (no) | 269 |
Page | pp.pp.- |
#Pages | 6 |
Date of Issue |