212. A Scenario-Based Solution Approach for a Stochastic Operating Room Allocation Problem
Invited abstract in session WC-8: Patient Flow Optimization, stream Health Care Management.
Wednesday, 13:30-15:00Room: H8
Authors (first author is the speaker)
| 1. | Duygu Tas
|
| Faculty of Engineering and Natural Sciences, Sabanci University | |
| 2. | Raf Jans
|
| Department of Logistics and Operations Management , HEC Montreal |
Abstract
This study addresses an operating room (OR) allocation problem where surgery durations are stochastic and the planning horizon spans multiple periods (e.g., five days). The inherent uncertainty in surgery durations may lead to delays in surgery start times and cause ORs to exceed their capacity. To tackle these challenges, we propose a model that incorporates both the fixed costs of opening ORs and the penalty costs related to expected overtime of ORs and expected delays in surgery start times. These expected values are exactly computed using a procedure that (i) assumes surgery durations follow a given probability distribution and (ii) applies the hospital’s "to-follow" policy. In this policy, commonly used in real-world hospital settings, once a surgery is completed in an OR, the next scheduled surgery starts immediately with no waiting time between surgeries. To solve this stochastic problem, we introduce a scenario-based approach, using a two-stage stochastic programming model that is solved based on a set of sample scenarios. We conduct computational experiments on newly generated instances, followed by extensive analysis of the results.
Keywords
- Health Care
- Scheduling
- Stochastic Programming
Status: accepted
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