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作 者:马颢洲 刘冉[1] MA Hao-zhou;LIU Ran(Department of Industrial Engineering&Management,Shanghai Jiao Tong University,Shanghai 200240,China)
机构地区:[1]上海交通大学工业工程与管理系,上海200240
出 处:《控制与决策》2025年第4期1172-1180,共9页Control and Decision
基 金:国家自然科学基金面上项目(72371161)。
摘 要:伴随线上医疗不断发展,医院在线上线下联合医疗服务的模式中面临着对线上服务医生进行排班优化决策的问题,其主要挑战在于时变的患者需求和线上医疗特殊的服务模式.针对此决策问题,首先将线上医疗服务系统建模为资源共享队列,采用时变马尔可夫链和均匀化方法对患者逗留时间、队列长度和医生加班时间进行建模和分析评估;然后基于以上系统评估方法,提出变邻域搜索的启发式算法对医生排班问题进行求解;最后基于合作医院的实际数据开展数值实验分析,以验证基于时变马尔可夫链建模的准确性.结果表明,所提出算法可以得到相对医院实际方案更好的排班结果,从而可以更加合理地安排医生工作时间,减少患者逗留时间,控制系统中的患者数量,并具有优良的鲁棒性.所做的研究对于完善我国线上医疗服务系统的运作管理具有实际意义.The continuous development of online medical has confronted hospitals with the problem of how to allocate physician resources in joint online and offline medical service systems,whose main challenges lie in the time-varying demand and the different service models of online medical.To address the physician scheduling problem in the online medical service system,the online medical service system is modeled as a processor-sharing queue firstly,and the timevarying Markov chain and uniformization methods are used to analyze and evaluate the patient sojourn time,queue length,and physician overtime time.Then,based on the uniformization method,a heuristic algorithm for variableneighborhood search is proposed.Finally,numerical experimental analysis is carried out based on the actual data of the cooperative hospital,which verifies the accuracy of the time-varying Markov chain based modeling,and proves that the proposed algorithm can obtain better scheduling results relative to the actual scheduling of the hospital,so that it can more reasonably arrange the working time of the physicians,reduce the sojourn time of the patients,and control the number of patients in the system,and has excellent robustness.The study has practical significance for improving the operation and management of online medical service systems in China.
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