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Efficient optimization algorithms for surgical scheduling under uncertainty

Shing Chih Tsai, Yingchieh Yeh and Chen Yun Kuo

European Journal of Operational Research, 2021, vol. 293, issue 2, 579-593

Abstract: In this paper, we develop a stochastic optimization model for a surgical scheduling problem considering a single operating room. We arrange a set of elective surgeries into appropriate time blocks, and determine their planned start time and specific sequence. Due to the complexity of the original formulation, we reformulate our model as a two-stage mixed-integer problem. We consider the planning decision in the first stage and the sequencing decision in the second stage (based on the first one). The goal of this paper is to obtain a nearly optimal schedule in reasonable computational time. The term “optimal” is defined as the lowest surgically related cost while achieving the given threshold with respect to some specific deterministic or stochastic performance measures.

Keywords: OR in healthcare; Surgery scheduling under uncertainty; Surgery planned start time; Simulation optimization; Laplace transform (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:293:y:2021:i:2:p:579-593

DOI: 10.1016/j.ejor.2020.12.048

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European Journal of Operational Research is currently edited by Roman Slowinski, Jesus Artalejo, Jean-Charles. Billaut, Robert Dyson and Lorenzo Peccati

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