Establishment of Evolutionary Nurse Scheduling Based on Self-aggregated Subspaces Mining
Project/Area Number |
21700264
|
Research Category |
Grant-in-Aid for Young Scientists (B)
|
Allocation Type | Single-year Grants |
Research Field |
Sensitivity informatics/Soft computing
|
Research Institution | Ube National College of Technology |
Principal Investigator |
KUBOTA Ryosuke 宇部工業高等専門学校, 制御情報工学科, 助教 (50432745)
|
Project Period (FY) |
2009 – 2011
|
Project Status |
Completed (Fiscal Year 2011)
|
Budget Amount *help |
¥3,250,000 (Direct Cost: ¥2,500,000、Indirect Cost: ¥750,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2009: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
|
Keywords | 遺伝的アルゴリズム / 自己組織化マップ / 粒子群最適化法 / 分散遺伝的アルゴリズム / ナース・スケジューリング / 確率的近傍埋め込み法 |
Research Abstract |
The purpose of this research is an establishment of a novel evolutionary computing method in order to solve a nurse scheduling problem, which is one of the optimization problems. Concretely, a genetic algorithm with self-organizing map-based selection method was proposed and enables a 2-dimensional visualization of characteristics of the given optimization problem. Furthermore, a particle swarm optimization and a distributed genetic algorithm were modified, and their effectiveness and validities were confirmed.
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Report
(4 results)
Research Products
(18 results)