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Adaptive layout for operating theatre in hospitals: different mathematical models for optimal layouts

Abstract : The adaptive layout for operating theatre (ALOT) problem in hospitals seeks to determine the ‘most efficient’ layout placement of a set of health-care operating facilities, corridors and elevators in a designated area subject to a set of constraints on professional standards. Such standards include regulations on: hygiene, safety and security of stakeholders (doctors, medical staff, patients and visitors); movements of technologies; and specifications of operating rooms (functions, orientations, space sizes, and desired closeness). Existing ALOT layouts are mostly generated from designs based on experiential judgments of experts. Due to the lack of scientific rigor and huge impact of layout design on the efficiency and effectiveness of an operating theater, the paper proposes mixed integer linear programming models to find optimal layouts under three different design variants: ALOT with multiple sections; ALOT with multiple rows and ALOT with multiple floors. Each variant has different demands for personnel, patients, and technologies over a planning horizon. Operating facilities can exchange functions at rearrangement costs from one period to another to meet the changing demands. The general objective consists of two sub-objectives: the first sub-objective is to minimize the total sum of the rearrangement and travel costs whereas the second sub-objective is to maximize the total sum of desired closeness among facilities. Computational experiences are presented on a set of quasi-real data instances for a hospital in France. They demonstrate the effectiveness of the formulations in providing optimal layouts for realistic-sized instances. Conclusion and future research directions are presented.
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Submitted on : Monday, October 25, 2021 - 10:08:08 AM
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Abdelahad Chraibi, Said Kharraja, Ibrahim H. Osman. Adaptive layout for operating theatre in hospitals: different mathematical models for optimal layouts. Annals of Operations Research, Springer Verlag, 2018, 272 (1-2), pp.493-527. ⟨10.1007/s10479-018-2799-x⟩. ⟨hal-03400636⟩

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