Optimization of the health examination scheduling problems using multi-objective genetic algorithms

Traditionally, the health examination scheduling (HES) is manually made by nurses or administrative assistants according to the practical examination situations reported from the medical personnel and the on-site examinees. However, the scheduling results of the man-made plan are usually rough, and hence it is hard to a complete schedule containing the detailed examination time, items and orders. The poor quality of the examination schedule often results in both the waste of medical resources and the bad service. Therefore, the purpose of this paper is to propose an intelligent and automatic approach to solve the HES problem. Our approach adopts a multiobjective genetic algorithm (MOGA) to simultaneously consider various HES management issues and provides a better scheduling plan for the HES problem.