Sequential Approximate Multiobjective Robust Optimization using ComputationalIntelligence and its Applications to Engineering Problems
| Project/Area Number |
22510164
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Social systems engineering/Safety system
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| Research Institution | Konan University |
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Principal Investigator |
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2012: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2011: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2010: ¥2,340,000 (Direct Cost: ¥1,800,000、Indirect Cost: ¥540,000)
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| Keywords | 多目的最適化 / ロバスト最適化 / 逐次近似最適化 / 計算知能 / パレート最適 / メタモデル / 遂次近似最適化 / 工学設計 |
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| Research Abstract |
In many practical engineering problems, objective functions can not be given explicitly in terms of design variables, but the solution is searched in parallel with refining the mathematical model adding experimental samples sequentially. Therefore, model errors appear inevitably. In addition, implementation errors are also inevitable in practical problems. On this circumstance, it is desirable to obtain a solution which is optimal and robust in the sense that is insensitive against those errors. In this research, robust multiobjective optimization is studied under sequential approximate modeling using computational intelligence.
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Report
(4 results)
Research Products
(34 results)
