| Project/Area Number |
21700252
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Osaka University |
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Principal Investigator |
TATSUMI Keiji 大阪大学, 大学院・工学研究科, 准教授 (30304017)
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| Project Period (FY) |
2009 – 2011
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| Project Status |
Completed (Fiscal Year 2011)
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| Budget Amount *help |
¥2,860,000 (Direct Cost: ¥2,200,000、Indirect Cost: ¥660,000)
Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2010: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2009: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
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| Keywords | 大域的最適化 / カオスダイナミクス / メタヒューリスティックス / パーティクル・スウォーム最適化法 / パーティクルスォーム最適化法 / メタヒューリスティクス / 群知能 / パーテクルスォーム最適化法 |
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| Research Abstract |
In this research, the chaoticness of the perturbation-based gradient model was shown under weaker assumptions, which can be used to solve the optimization problem. In addition, new particle swarm optimization(PSO) models were proposed, in which the perturbation-based model is exploited to restart stagnated particles or to update particles' positions according to the distances between their two best solutions, and their effectiveness were shown by the numerical experiments. Moreover, sufficient conditions of chaoticness of the both models were derived by making use of the structure of the PSOs, which is more useful than the conditions for the general metaheuristics.
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