Constraint satisfaction in logic programming
Constraint satisfaction in logic programming
Solving large combinatorial problems in logic programming
Journal of Logic Programming - Logic programming applications
A scheduling model for hospital residents
Journal of Medical Systems
A multi-objective programming model for scheduling emergency medicine residents
Computers and Industrial Engineering
Constraint programming based column generation for employee timetabling
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
CPAIOR'05 Proceedings of the Second international conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems
A goal programming model for scheduling residents in an anesthesia and reanimation department
Expert Systems with Applications: An International Journal
A hierarchical goal programming model for scheduling the outpatient clinics
Expert Systems with Applications: An International Journal
Hi-index | 0.01 |
Persistent calls come from within the graduate medical education community and from external sources for regulating the resident duty hours in order to meet the obligations about the quality of resident education, the well-being of residents themselves, and the quality of patient care services. The report of the Accreditation Council for Graduate Medical Education (ACGME) proposes common program requirements for resident hours. In this paper, we first develop a mixed-integer programming model for scheduling residents' duty hours considering the on-call night, day-off, rest period, and total work-hour ACGME regulations as well as the demand coverage requirements of the residency program. Subsequently, we propose a column generation model that consists of a master problem and an auxiliary problem. The master problem finds a configuration of individual schedules that minimizes the sum of deviations from the desired service levels for the day and night periods. The formulation of this problem is possible by representing the feasible schedules using column variables, whereas the auxiliary problem finds the whole set of feasible schedules using constraint programming. The proposed approach has been tested on a series of problems using real data obtained from a hospital. The results indicate that high-quality schedules can be obtained within a few seconds.