面向多檢查的門診患者調(diào)度研究
[Abstract]:Timely examination is very important for the diagnosis and treatment of the patient's condition. However, the different emergency degree of patients, the diversity of examination items, and the behavioral factors of patients, such as failure, make it difficult to solve the problem of outpatient scheduling. In order to solve this problem, a finite time domain Markov decision process (MDP) model is established in this paper, considering the different needs of patients for two kinds of examination items, two kinds of different emergency levels, and the patient's failure and doctors' overtime. The goal is to maximize the expected return from patient testing and minimize the penalty cost of expected overtime. Because of the complexity of MDP model, it is difficult to analyze the optimal control strategy by analytic method. Therefore, based on the numerical experiment of MDP model, the structural characteristics of the optimal solution are observed, and two parameterized heuristic scheduling strategies are further constructed. Genetic algorithm is used to optimize the parameters of scheduling policy. Numerical experiments have compared the optimal control strategy, two heuristic scheduling strategies and the first-come first served rule. The experimental results show that the proposed scheduling policy performance deviates from the optimal solution by less than 10 percent, and when the workload is very heavy, The heuristic scheduling strategy is much better than the first come first served rule.
【作者單位】: 上海交通大學(xué)工業(yè)工程與管理系;
【基金】:國家自然科學(xué)基金資助項(xiàng)目(71471113)
【分類號】:O225;R197.3
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