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

Abstract

Purpose: This paper aims to propose an optimal scheduling for medical resources order and shipment in community health service centers (CHSCs).

Design/methodology/approach: This paper presents two logistical support models for scheduling medical resources in CHSCs. The first model is a deterministic planning model (DM), which systematically considers the demands for various kinds of medical resources, the lead time of supplier, the storage capacity and other constraints, as well as 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 demand for medical resources is always stochastic in practice, the second model is constructed as a stochastic programming model (SM). A solution procedure is developed to solve the proposed two models and a simulation-based evaluation method is proposed to compare the performances of the proposed models. Findings and

Findings: The main contributions of this paper includes the following two aspects: (1) While most research on medical resources optimization studies a static problem taking no consideration of the time evolution and especially the dynamic demand for such resources, the proposed models in our paper integrate time-space network technique, which can find the optimal scheduling of logistical support for medical resources order and shipment in CHSCs effectively. (2) The logistics plans in response to the deterministic demand and the time-varying demand are constructed as 0-1 mixed integer programming model and stochastic integer programming model, respectively. The optimal solutions not only minimize the operation cost of the logistics system, but also can improve the order and shipment operation in practice.

Originality/value: Currently, medical resources in CHSCs are purchased by telephone or e-mail. The important parameters in decision making, i.e. order/shipment frequency and order quantity, are manually determined by the staff with experience according to the average demand in the past years/months. The planned schedules may not be efficient, or may not be at all feasible to satisfy all demands since a large portion of customer service requests in CHSCs are uncertain and tine-varying. The proposed methods in this paper could be effective ways in solving the problems in practice.