Parameter Decision Method of Chaotic Search for Combinatorial Optimization Problem
| Project/Area Number |
25870770
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Soft computing
Social systems engineering/Safety system
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| Research Institution | Nippon Institute of Technology (2014)
Tokyo University of Science (2013) |
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Principal Investigator |
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| Project Period (FY) |
2013-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥520,000 (Direct Cost: ¥400,000、Indirect Cost: ¥120,000)
Fiscal Year 2013: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 組合せ最適化問題 / 発見的解法 / カオスニューラルネットワーク / ソフトコンピューティング / メタ戦略 / ヒューリスティック解法 |
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| Outline of Final Research Achievements |
For finding near optimal solutions of NP-hard combinatorial optimization problems, a chaotic search method has been proposed. In the method, a chaotic neural network is constructed by chaotic neurons. We have already clarified that its high searching ability depends on a statistical property of refractory effects in the chaotic neuron. However it is difficult to find optimal parameters of the refractory effect. In order to develop a method that decides optimal parameters, we confirmed relation between the values of parameters and searching abilities of the chaotic search method or a dynamics of the chaotic neuron from some numerical experiments.
We analyzed relation the searching ability and Lyapunov exponent of a single chaotic neuron. A positive Lyapunov exponent indicates that a behavior of the chaotic neuron is chaos. From some numerical experiments, we confirmed that if the Lyapunov exponents are positive, good results are obtained for a motif extraction problem.
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Report
(3 results)
Research Products
(9 results)
