A Genetic Algorithm for the Optimization of Admission Scheduling Strategy in Hospitals

Abstract

Decisions for admission scheduling in hospitals are a class of optimization problems constrained by many factors. Instead of scheduling the admission of patients directly, this paper proposes a genetic algorithm (GA) designed for the optimization of a long-term admission strategy for the ophthalmology department in hospitals. For the optimization of admission strategy, we devise a coding scheme of strategies and define the objective functions for two objectives: efficiency and fairness. The proposed algorithm utilizes historical data of the hospital for evaluation of chromosomes. Experiments are conducted on several cases, and the strategy optimized by the proposed GA is compared with the first come first serve (FCFS) strategy and the greedy strategy. Experimental results show that strategies optimized by the proposed algorithm outperform FCFS and the greedy strategy.