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Adaptive Elective Surgery Planning Under Duration and Length-Of-Stay Uncertainty: A Robust Optimization Approach

Saba Neyshabouri (sneyshab***at***gmu.edu)
Bjorn Berg (berg.bjorn***at***mayo.edu)

Abstract: Scheduling elective surgeries is a complicated task due to the coupled effect of multiple sources of uncertainty and the impact of the proposed schedule on the downstream units. In this paper, we propose an adaptive robust optimization model to address the existing uncertainty in surgery duration and length-of-stay in the surgical intensive care unit. The framework allows for the decision-maker to adjust the level of risk she/he is comfortable. We propose the adapted column-and-constraint generation method to obtain exact solutions for the proposed formulation. The performance and the quality of our proposed solution methodology are tested through computational experiments and simulation modeling.

Keywords: Robust optimization, Surgery scheduling, Length-of-stay, Downstream resource constraint

Category 1: Robust Optimization

Category 2: Applications -- OR and Management Sciences (Scheduling )

Category 3: Integer Programming (Cutting Plane Approaches )

Citation: Saba Neyshabouri, Bjorn Berg,Technical report, "Adaptive Elective Surgery Planning Under Duration and Length-Of-Stay Uncertainty: A Robust Optimization Approach", 09/2015

Download: [PDF]

Entry Submitted: 09/29/2015
Entry Accepted: 09/29/2015
Entry Last Modified: 10/03/2015

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