Development of Hierarchical Evolutionary Computation Method Solving Large-scale Nurse Scheduling Problem
| Project/Area Number |
15K00356
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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 | Ube National College of Technology |
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Principal Investigator |
Kubota Ryosuke 宇部工業高等専門学校, 制御情報工学科, 教授 (50432745)
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| Co-Investigator(Kenkyū-buntansha) |
堀尾 恵一 九州工業大学, 大学院生命体工学研究科, 准教授 (70363413)
三澤 秀明 宇部工業高等専門学校, 電気工学科, 准教授 (40636099)
石川 秀大 大分工業高等専門学校, 情報工学科, 助教 (60780989)
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| Project Period (FY) |
2015-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2017: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2016: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 進化的計算法 / 階層型遺伝的アルゴリズム / 花火アルゴリズム / 遺伝的アルゴリズム / 差分進化アルゴリズム / ナース・スケジューリング / 階層型進化的計算法 |
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| Outline of Final Research Achievements |
In this research, a new hierarchical evolutionary computation algorithm has proposed. In the proposed method, optimization problem is divided into several levels of hierarchy. The proposed method realized more effective search than the conventional method. Further, the general versatility of the proposed algorithm has been investigated. Additionally, the effective and stable search has been realized by dividing the population into several sub-population.
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Report
(4 results)
Research Products
(10 results)
