標題: 台灣教學醫院牙科醫師排班決策—理論與實證
Resident and Intern Rostering at a Dental Department in Taiwan
作者: 穆俊廷
Mu, Chun-Ting
陳文智
Chen, Wen-Chih
工業工程與管理系所
關鍵字: 排班問題;混整數規劃;基因演算法;決策支援工具;rostering problem;mixed-integer programming;genetic algorithm;decision support tool
公開日期: 2013
摘要: 本研究探討台北市某教學醫院牙科部住院醫師與實習醫師的排班問題。排班時,除必須滿足相關限制條件以及不同資歷醫師的不同工作規範等因素外,最重要的是要考量醫師工作上的方便性。案例醫院過去以人工方式進行每月例行排班任務時,需要耗費大量時間。針對此實際問題,本研究建立一混整數規劃數學模型,並以基因演算法求解,能在極短時間內正確地完成排班任務。此外,基於「使用者導向」原則,我們把提出的求解方法與過去使用者慣用的Excel試算表介面整合,以期最小化導入與適應新系統的成本與使用時的計算成本。我們由案例經驗中發現,排班實務首重如何快速找到可行解,而非傳統文獻所重視的尋求最佳解。
Based on a real case, this work investigates a resident and intern rostering problem at a dental department in Taiwan. The resident and intern rostering decision is a monthly routine task but very time consuming. We formulate the rostering problem as a mixed-integer programming problem, and solve it by the genetic algorithm (GA). We integrate the proposed method with the existing user interfaces as a spreadsheet-based tool. This thesis shows how OR techniques can really help in the health care practices, and shares the experiences to work with practitioners in the health systems.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT070153331
http://hdl.handle.net/11536/74578
Appears in Collections:Thesis