A multi-objective programming model for scheduling emergency medicine residents

Topaloglu Ş. A.

COMPUTERS & INDUSTRIAL ENGINEERING, vol.51, no.3, pp.375-388, 2006 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 51 Issue: 3
  • Publication Date: 2006
  • Doi Number: 10.1016/j.cie.2006.08.003
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.375-388
  • Keywords: resident scheduling, emergency medicine resident, personnel scheduling, goal programming, emergency room, analytical hierarchy process, SUPPORT-SYSTEM, TABU SEARCH, NURSE, SLEEP
  • Dokuz Eylül University Affiliated: Yes


Scheduling emergency medicine residents (EMRs) is a complex task, which considers a large number of rules (often conflicting) related to various aspects such as limits on the number of consecutive work hours, number of day and night shifts that should be worked by each resident, resident staffing requirements according to seniority levels for the day and night shifts, restrictions on the number of consecutive day and night shifts assigned, vacation periods, weekend off requests, and fair distribution of responsibilities among the residents. Emergency rooms (ERs) are stressful workplaces, and in addition shift work is well-known to be more demanding than regular daytime work. For this reason, preparing schedules that suit the working rules for EMRs is especially important for reducing the negative impact on shift workers physiologically, psychologically, and socially. In this paper, we present a goal programming (GP) model that accommodates both hard and soft constraints for a monthly planning horizon. The hard constraints should be adhered to strictly, whereas the soft constraints can be violated when necessary. The relative importance values of the soft constraints have been computed by the analytical hierarchy process (AHP), which are used as coefficients of the deviations from the soft constraints in the objective function. The model has been tested in the ER of a major local university hospital. The main conclusions of the study are that problems of realistic size can be solved quickly and the generated schedules have very high qualities compared to the manually prepared schedules, which require a lot of effort and time from the chief resident who is responsible for this duty. (c) 2006 Elsevier Ltd. All rights reserved.