Optimal scheduling of logistical support for medical resources order and shipment in community health service centers

Purpose: Medical resources scheduling affects the medical institution's operation cost, customer satisfaction and medical service quality. Therefore, a lean arrangement of medical resources order and shipment is quite necessary and important. In this paper, we propose two optimal models for medical resources order and shipment in community health service centers (CHSCs), with a dual emphasis on minimizing the total operation cost and improving the operation level in practice. Design/methodology/approach: The first planning model is a deterministic planning model (DM). Systematically, it considers constraints including the lead time of the suppliers, the storage capacity of the medical institutions, and the integrated shipment planning in the dimensions of time and space. The problem is a multi-commodities flow problem and is formulated as a mixed 0-1 integer programming model. Considering the stochastic demand, the second model is constructed as a stochastic programming model (SM). A solution procedure is developed to solve the two models and a simulation-based evaluation method is presented to compare the performances of the proposed models. Findings: The main contributions of this paper include the following two aspects: (1) most research on medical resources allocation studies a static problem taking no consideration of the time evolution and the time-varying demand. In this paper, time-space network technique is adopted to depict the logistics situation in CHSCs from both time and space dimensions. (2) the logistics plans in response to the deterministic demand and the time-varying demand are constructed as a 0-1 mixed integer programming model and a stochastic integer programming model, respectively. The optimal solutions can not only minimize the total operation cost, but also improve the order and shipment operation in practice. Originality/value: Generally, medical resources in CHSCs are purchased by telephone or email. The important parameters in decision making, i.e., order/shipment frequency and order quantity, are manually determined by the decision maker based upon his/her experience. The planned schedules may not be efficient or feasible to satisfy all demands since a large portion of customer requests are uncertain and time-varying. The proposed methods in this paper could be effective in solving the problems in actual operations.