Extremely large-scale optimization problem-solving using robust and scalable evolutionary computation
| Project/Area Number |
22500196
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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 |
Sensitivity informatics/Soft computing
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| Research Institution | Hokkaido University |
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Principal Investigator |
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| Project Period (FY) |
2010-04-01 – 2014-03-31
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| Project Status |
Completed (Fiscal Year 2013)
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| Budget Amount *help |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2013: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2012: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2011: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2010: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 進化計算 / 大規模並列化 / メニーコア / GPGPU |
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| Research Abstract |
We have developed a series of evolutionary algorithms such as BOA-MD, an extension of BOA introducing mixture distributions, BHCS by combining BOA with local search, ARGA and BRGA for MINLP (Mixed-Interger Non-Linear Programming). We also developed large-scale parallel evolutionary algorithms in a many core architecture and cloud computing environment.
As applications to real-world problems, we applied evolutionary algorithms to optimal resource allocation problem in cloud computing environment as a MINLP problem, de novo ligand docking problems to find promising structures of medicines automatically, and so on, to show the effectiveness of our approach.
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Report
(5 results)
Research Products
(58 results)
