基于马尔科夫链的紧急医疗系统运作优化

Operation Optimization of Emergency Medical System Based on Markov Chain

紧急医疗系统由急救中心、救护车站和医院组成,通常存在救护车卸载延迟、急诊科室患者等待时间过长以及抢救室病床数量不合理等问题。为了优化此系统,利用连续时间马尔科夫链方法进行系统建模,得到医院急诊科救护车排队队长等变量的解析公式。在此基础上,从急救中心和医院双方角度出发分别建立其运作优化模型,并设计禁忌搜索等启发式算法求解。然后进行协同优化,分析了双方交替优化各自目标直至收敛后的均衡状态。数值实验中将实际方案与模型求解结果对比,验证了系统运作优化结果的优势。

The emergency medical system consists of emergency center,ambulance stations and hospitals.It has problems such as ambulance offload delay,patients′over-waiting in emergency departments and the unreasonable number of emergency beds.The continuous time Markov chain method was used to establish an analytical model of the system and to evaluate the system average ambulance queue length.Two mathematical models were formulated for operational optimization of emergency center and hospital emergency departments,and meta-heuristic algorithms like Tabu search were introduced to solve the two models.Then collaborative optimization was performed,both sides alternately optimized their respective goals until convergence and the equilibrium state was analyzed.Numerical experiments show the advantages of the proposed model and method compared with the actual scheme.