運用啟發式演算法解跨醫院人力配置排班問題

Applying meta-heuristics to solve inter-hospital staff allocation and scheduling problems

江宗恒(Tsung-Huan Chiang)

指導教授 ： 陳平舜

中原大學/工學院/工業工程研究所/碩士(2014年)

https://doi.org/10.6840/cycu201400440

摘要

醫院管理牽涉到醫療資源配置，由於不同規模的醫院對醫療人力的需求不同，加上每位醫療人員能照顧的病患人數有限，醫院為了滿足病患就醫的需求，需要謹慎評估醫療人力的配置。且醫院每位醫療人員之能力、政府法規和各醫院排班規定有所不同，因此對於如何有效的解決醫療人力配置為醫院管理的重要議題。
本研究的研究目的是探討醫療人力配置規劃，且又同時解決排班問題。此排班問題考慮醫療人員排班偏好的權重，且需符合各醫院的限制與需求。本研究建構跨醫院醫療人力配置班表，以降低醫療人員對班表的不滿意度。
本研究的研究方法是發展粒子群演算法結合三種啟發式演算法，對排班進行求解，並將多餘的人力做配置，以快速求得符合決策目標的近似最佳解，其結果不僅可解決在協同醫院下跨醫院醫療人力配置排班問題，也可減少醫療人力之閒置。因此，本研究除可提供醫院評鑑機構去評量醫療人力配置水準外，也可作為管理者對於跨醫院的醫療人力配置班表為參考依據。

關鍵字

啟發式演算法 ； 粒子群演算法 ； 醫療人員排班 ； 人力配置

並列摘要

Hospital management involves the allocation of medical resources. Since different scales of hospitals require different types of medical staff and each medical staff only takes care limited number of patients, hospitals require evaluating the allocation of medical staff carefully in order to meet the needs of patients. However, personnel ability, government regulations and hospital scheduling regulations depend on hospitals. Therefore, the decisions of determining medical staff allocation become an important task for hospital management.
The purpose of this research was to develop a medical staff allocation plan, and solve a medical scheduling problem. The medical scheduling problem included the preferences of medical staff and the requirements and limitations of each hospital. This research constructed a cross-hospital medical staff schedule. By doing this, the dissatisfaction of medical staff at their monthly schedule can be reduced.
The methodology of this study was to develop a combination of the particle swarm optimization (PSO) and three heuristic algorithms to solve the medical staff scheduling problem, to reallocate excess medical staff, and to quickly get an approximate optimal solution based on the medical staff’s preferences. The result of this research not only could solve the inter-hospital medical staff scheduling problem, but also could reduce the idleness of medical staff resources. Further, this study could provide hospital accreditation agencies to access the level of established medical staff of hospitals, and could provide an inter-hospital medical staff schedule for hospital managers as a reference.

並列關鍵字

Medical staff scheduling ； Staff allocation ； Particle swarm optimization (PSO) ； Heuristic algorithm

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