| Project/Area Number |
24700237
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| Research Category |
Grant-in-Aid for Young Scientists (B)
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| Allocation Type | Multi-year Fund |
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| Research Field |
Sensitivity informatics/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, 准教授 (50432745)
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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 |
¥4,290,000 (Direct Cost: ¥3,300,000、Indirect Cost: ¥990,000)
Fiscal Year 2014: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
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| Keywords | ナース・スケジューリング / 進化的計算法 / 遺伝的アルゴリズム / レーベンシュタイン距離 / 粒子群最適化法 / 確率的近傍埋め込み法 |
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| Outline of Final Research Achievements |
In this research, a new nurse-scheduling algorithm has proposed. The proposed method uses blocks of locally symbolic pattern of elements in a shift roster. The similarity between blocks is represented by Levenshtein distance. In the proposed method, a modified genetic algorithm realizes the nurse scheduling. The modified genetic algorithm uses the modified fitness function for evaluating the interdictory shift patterns and the number of days of the sustained shiftwork. Furthermore, the proposed method changes the crossover and mutation rates adaptively in accordance with the searching progress. Through the experiments, it was observed that the proposed method could generate the shift roster satisfied the guideline on the nurses’ shiftwork perfectly. Furthermore, the average satisfaction rate for all nurses’ requests was 79.4%.
In addition, fundamental searching performances of genetic algorithm and particle swarm optimization have also been improved.
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