Development of an adaptive learning type optimization method based on evolutionary systems and application to reconfiguable device design
| Project/Area Number |
24560494
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
System engineering
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| Research Institution | Chiba University |
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Principal Investigator |
KOAKUTSU Seiichi 千葉大学, 工学(系)研究科(研究院), 教授 (70241940)
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| Co-Investigator(Kenkyū-buntansha) |
OKAMOTO Takashi 千葉大学, 大学院工学研究科, 准教授 (40451752)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥3,640,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥840,000)
Fiscal Year 2014: ¥260,000 (Direct Cost: ¥200,000、Indirect Cost: ¥60,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 最適化手法 / 進化型計算法 / 再構成可能デバイス / 二次割当問題 / 進化計算 |
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| Outline of Final Research Achievements |
This research aims at a development of an adaptive learning type optimization technique that adjusts its search process based on the structure of a cost function. The developed technique is applied to combinatorial optimization problems such as design problems of reconfiguable device which have a large-scale and complex cost function. In the developed technique, information on the structure of the cost function is collected in the process of optimization, and it is used to adjust the search process of the solution. The developed technique is effective to quality improvement of the solution and shortening at computation time. As a result, the solution of the high quality comes to be obtained efficiently without adjusting the programs of each problem by hand, and without depending on the scale and modeling of problems.
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Report
(4 results)
Research Products
(35 results)
