| Project/Area Number |
26330269
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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 |
Soft computing
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| Research Institution | Muroran Institute of Technology |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
榊原 一紀 富山県立大学, 工学部, 准教授 (30388110)
廣安 知之 同志社大学, 生命医科学部, 教授 (20298144)
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| Project Period (FY) |
2014-04-01 – 2017-03-31
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| Project Status |
Completed (Fiscal Year 2016)
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| Budget Amount *help |
¥4,030,000 (Direct Cost: ¥3,100,000、Indirect Cost: ¥930,000)
Fiscal Year 2016: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | 進化型多目的最適化 / 大規模問題 / 組み合わせ最適化 / 解分析 / Nurse Scheduling Problem / Vehicle Routing Problem / 大規模組合わせ最適化問題 / 大規模組み合わせ問題 / 看護師勤務表作成問題 |
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| Outline of Final Research Achievements |
New evolutionary multi-criterion optimization (EMO) approaches specified for very large scale combinatorial optimization problems has been developed. In this research, we picked vehicle routing problem (VRP）and nurse scheduling problem (NSP) up, and new EMO approaches considering the characteristic of each problem were developed. Through numerical experiments, the effectiveness of these approaches could be verified.
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