Abstract
We formulated a new stochastic programming formulation to solve the dynamic scheduling problem in a given set of elective surgeries in the day of operation. The problem is complicated by the fact that the exact surgery durations are not known in advance. Elective surgeries could be performed in parallel in a subset of operating rooms. The appointment times and assignments of surgeries were planned by an experienced nurses in advance. We present a mathematical model to capture the nature of dynamic scheduling problem. We propose an efficient solution based on an improved genetic algorithm (IGA). Our numerical results showed that dynamic scheduling with the IGA improves the resource utilization as measured by surgeon waiting time and operation room idle time.
Highlights
High-quality medical resources in China are scarce, and the inefficient use of medical resources makes the scarcity crisis even severer
Results. is section presents the results of the experiments to illustrate the structure of the optimal schedule for a specific example and evaluate the performance of the proposed method in different problem instances. e proposed algorithm was coded in MATLAB R2013a. e experiments were conducted on Intel Core i7 PC at 2.40 GHz with 4 GB memory. e instances of this paper were derived from field observations in Shanghai First People’s Hospital
We describe the dynamic scheduling process as a series of discrete events
Summary
High-quality medical resources in China are scarce, and the inefficient use of medical resources makes the scarcity crisis even severer. Surgeries require several medical resources, including operating rooms and human resources [1, 2]. Surgeries are often classified into elective surgery and urgent surgery. Urgent surgeries cannot be planned in advance because of their uncertain nature, and they must be scheduled on a much shorter notice because of the higher priority of urgent surgeries. E resources are not shared between elective and urgent surgeries. Urgent surgeries are not taken into consideration in generating a schedule for elective surgeries
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