Mixed-integer linear programming, constraint programming and column generation approaches for operating room planning under block strategy

•We consider the planning and scheduling of operating rooms under block strategy.•The preferences of patients, surgeons and hospital managers are considered.•The CP and CPCG methods outperform the linear programming models in terms of computational time.•A sensitivity analysis is done on the main pa...

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Bibliographic Details
Published in:Applied Mathematical Modelling Vol. 105; pp. 438 - 453
Main Authors: Ghandehari, Najmeh, Kianfar, Kamran
Format: Journal Article
Language:English
Published: New York Elsevier Inc 01.05.2022
Elsevier BV
Subjects:
Block strategy
Column generation
Computing time
Constraint modelling
Constraint programming
Costs
Integer programming
Linear programming
Master surgery schedule
Mixed integer
Mixed-integer linear programming
Operating room planning
Optimization
Parameter sensitivity
Run time (computers)
Sensitivity analysis
Strategy
Surgeons
Column generation
Block strategy
Operating room planning
Constraint programming
Mixed-integer linear programming
Master surgery schedule
ISSN:0307-904X, 1088-8691, 0307-904X
Online Access:Get full text
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Summary:•We consider the planning and scheduling of operating rooms under block strategy.•The preferences of patients, surgeons and hospital managers are considered.•The CP and CPCG methods outperform the linear programming models in terms of computational time.•A sensitivity analysis is done on the main parameters of the problem.•The unit waiting cost of patients is the most sensitive part of the objective function. The planning of operating rooms under block strategy is addressed in this study. The decisions are about opening the operating rooms and assigning specialties and surgeons to blocks at the tactical level, and sequencing the surgeries at the operational level. This problem aims to minimize the costs of opening the operating rooms and their overtime, the waiting costs of patients, and the surgeons' idle costs. We propose two mixed-integer linear programming models, a constraint programming (CP) model and a constraint programming-based column generation (CPCG) method for handling the problem. The performance of the models is evaluated by random test instances. The results indicate that CP and CPCG models are more efficient than the linear programming models in terms of computational time, and the number of variables and constraints. The proposed method CPCG generates optimal solutions for problem instances of up to 30 surgeries in less than 4 min. The CP model finds the optimal solutions in about one minute but proving the optimality of the found solutions is time-consuming in some instances. The maximum optimality gap for the proposed two-step linear programming model is 2%, while its run time is less than 20 s. A sensitivity analysis is done on the main parameters of the problem like objectives' weights, opening cost of ORs, unit waiting cost of patients, and the maximum available time in surgery blocks. Among the three objectives, the unit waiting cost of patients has the most sensitivity to variations of the objective function weights.
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ISSN:0307-904X
1088-8691
0307-904X
DOI:10.1016/j.apm.2022.01.001