Future paths for integer programming and links to artificial intelligence
Computers and Operations Research - Special issue: Applications of integer programming
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Branch-And-Price: Column Generation for Solving Huge Integer Programs
Operations Research
Applying adaptive algorithms to epistatic domains
IJCAI'85 Proceedings of the 9th international joint conference on Artificial intelligence - Volume 1
Single versus hybrid time horizons for open access scheduling
Computers and Industrial Engineering
A new heuristic algorithm for the operating room scheduling problem
Computers and Industrial Engineering
Ant colony algorithm for surgery scheduling problem
ICSI'12 Proceedings of the Third international conference on Advances in Swarm Intelligence - Volume Part I
A genetic algorithm for two-stage no-wait hybrid flow shop scheduling problem
Computers and Operations Research
Assessing the impact of stochasticity for operating theater sizing
Decision Support Systems
Multi-objective operating room scheduling considering desiderata of the surgical team
Decision Support Systems
On capacity allocation for operating rooms
Computers and Operations Research
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The objective of this paper is to design a weekly surgery schedule in an operating theatre where time blocks are reserved for surgeons rather than specialities. Both operating rooms and places in the recovery room are assumed to be multifunctional, and the objectives are to maximise the utilisation of the operating rooms, to minimise the overtime cost in the operating theatre, and to minimise the unexpected idle time between surgical cases. This weekly operating theatre planning and scheduling problem is solved in two phases. First, the planning problem is solved to give the date of surgery for each patient, allowing for the availability of operating rooms and surgeons. Then a daily scheduling problem is devised to determine the sequence of operations in each operating room in each day, taking into account the availability of recovery beds. The planning problem is described as a set-partitioning integer-programming model and is solved by a column-generation-based heuristic (CGBH) procedure. The daily scheduling problem, based on the results obtained in the planning phase, is treated as a two-stage hybrid flow-shop problem and solved by a hybrid genetic algorithm (HGA). Our results are compared with several actual surgery schedules in a Belgian university hospital, where time blocks have been assigned to either specific surgeons or specialities several months in advance. According to the comparison results, surgery schedules obtained by the proposed method have less idle time between surgical cases, much higher utilisation of operating rooms and produce less overtime.