With the diversity of work styles in recent years, we need to solve issues such as the aging of the working-age population and the increasing responsibilities of caregiving. In particular, the medical field requires efficient and appropriate scheduling due to the lengthening of working hours caused by the shortage of human resources. Many researchers have addressed the Nurse Scheduling Problem (NSP). However, the scheduling problem for medical doctors is more difficult than NSP because they have more varied work arrangements and more stringent constraints than those of the NSP. In this paper, we propose a method to automatically generate work scheduling that considers the work hours of medical doctors. The proposed method classifies medical doctors into four types of work arrangements (morning shift, afternoon shift, semi-night shift, and night shift) and constructs rules to generate constraints for each work arrangement. In addition, the proposed method uses a genetic algorithm to generate the optimal work schedules for multiple medical doctors considering computer resources in heuristic search. The evaluation results showed that the proposed method can generate work schedules that satisfy as many contraints as possible.

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A Genetic Algorithm-Based Scheduling Method Considering Working Hours for Medical Doctors

  • Subaru Narahashi,
  • Eiji Hirakawa,
  • Akira Uchiyama,
  • Yusuke Gotoh

摘要

With the diversity of work styles in recent years, we need to solve issues such as the aging of the working-age population and the increasing responsibilities of caregiving. In particular, the medical field requires efficient and appropriate scheduling due to the lengthening of working hours caused by the shortage of human resources. Many researchers have addressed the Nurse Scheduling Problem (NSP). However, the scheduling problem for medical doctors is more difficult than NSP because they have more varied work arrangements and more stringent constraints than those of the NSP. In this paper, we propose a method to automatically generate work scheduling that considers the work hours of medical doctors. The proposed method classifies medical doctors into four types of work arrangements (morning shift, afternoon shift, semi-night shift, and night shift) and constructs rules to generate constraints for each work arrangement. In addition, the proposed method uses a genetic algorithm to generate the optimal work schedules for multiple medical doctors considering computer resources in heuristic search. The evaluation results showed that the proposed method can generate work schedules that satisfy as many contraints as possible.