EconPapers    
Economics at your fingertips  
 

Operating room scheduling problem under uncertainty: Application of continuous phase-type distributions

Mohsen Varmazyar, Raha Akhavan-Tabatabaei, Nasser Salmasi and Mohammad Modarres

IISE Transactions, 2020, vol. 52, issue 2, 216-235

Abstract: This article studies the stochastic Operating Room (OR) scheduling problem integrated with a Post-Anesthesia Care Unit (PACU), the overall problem is called the Operating Theater Room (OTR) problem. Due to the inherent uncertainty in surgery duration and its consecutive PACU time, the completion time of a patient should be modeled as the sum of a number of random variables. Some researchers have proposed the use of the normal distribution for its well-known additive property, but there are questions regarding its fitting adequacy to real OTR data, which tends to be asymmetric with a long tail. We propose to estimate the surgery and PACU times with the family of Continuous PHase-type (CPH) distributions, which provides both fitting adequacy and additive property. We first compute the completion time of each patient analytically and compare the results with normal and lognormal distributions on a series of real OTR datasets. Then, we develop a search algorithm embedding a constructive heuristic and a meta-heuristic algorithm as a sequence generator engine for the patients, and apply the CPH distribution as a chance constraint to eventually find the schedule of each sequence in the OTR problem. The best algorithm among several tested constructive heuristic algorithms is used as the neighborhood structure of meta-heuristic algorithms. We finally construct a numerical example of OTR problem to illustrate the application of the proposed algorithm.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://hdl.handle.net/10.1080/24725854.2019.1628372 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:52:y:2020:i:2:p:216-235

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20

DOI: 10.1080/24725854.2019.1628372

Access Statistics for this article

IISE Transactions is currently edited by Jianjun Shi

More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:uiiexx:v:52:y:2020:i:2:p:216-235