Historical Data -Driven Nurse Flexible Scheduling Problem
作者单位：School of Business Administration Northeastern University Dept of Systems Engineering State Key Lab of Synthetic Automation of Process Industry College of Information Science & Engineering Northeastern University
会议名称：《第25届中国控制与决策会议》
会议届次：25th
主办单位：IEEE;NE Univ;IEEE Ind Elect Chapter;IEEE Harbin Sect Control Syst Soc Chapter;Guizhou Univ;IEEE Control Syst Soc;Syst Engn Soc China;Chinese Assoc Artificial Intelligence;Chinese Assoc Automat;Tech Comm Control Theory;Chinese Assoc Aeronaut;Automat Control Soc;Chinese Assoc Syst Simulat;Simulat Methods & Modeling Soc;Intelligent Control & Management Soc
会议日期：2013年
学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 07[理学] 070105[理学-运筹学与控制论] 0701[理学-数学]
基 金：supported by National Nature Science Foundation of China 71021061
关 键 词：Heuristic algorithm integer programming nurse flexible scheduling queuing theory time series forecasting
摘 要：The nurse scheduling problem （NSP） is a complex combinatorial optimization problem, we aim is to use the nurse resource reasonably. In this paper, firstly, with the method of time series analysis, an autoregressive integrated moving average （ARIMA） model is established to forecast the number of patients, which is used as input to calculate the volumes of nurse for scheduling by queuing theory. In the aspect of NSP, a comprehensive integer programming model considering nurse’s levels and their preferences to different shifts is established, with a series of labor regulations. Finally, in order to get a near-optimal scheduling, a heuristic algorithm combined with a series of transformation rules is designed. The contribution in this paper is threefold. Firstly, it satisfies all the constraints and obtains a near-optimal scheduling. Secondly, it can control patient waiting time validly. Thirdly, it can adjust the number of nurses to the shift dynamically.