Scheduling elective surgery patients considering time-dependent health urgency: Modeling and solution approaches

Joonyup Eun, Sang Phil Kim, Yuehwern Yih, Vikram Tiwari

Research output: Contribution to journalArticle

Abstract

This paper describes an operating room planning problem in which patients have different severity levels when they are diagnosed, and patient health condition deteriorates with the increase of waiting time. In addition, uncertainty in surgery durations is incorporated in this problem. A stochastic mixed integer program is proposed to optimize the assignment of surgeries considering the worst patient health condition among all patients waiting for surgeries and total overtime that exceeds the available time durations allotted for surgeries. This paper presents three solution approaches: the sample average approximation method, a fastest ascent local search, and a tabu search. These three solution approaches are evaluated in the computational study and the results show that the tabu search provides effective solutions within reasonable computation times.

Original languageEnglish
Pages (from-to)137-153
Number of pages17
JournalOmega (United Kingdom)
Volume86
DOIs
Publication statusPublished - 2019 Jul 1
Externally publishedYes

Fingerprint

Surgery
Modeling
Health
Tabu search
Overtime
Operating room
Planning
Assignment
Waiting time
Local search
Uncertainty
Mixed integer program
Severity
Sample average approximation

Keywords

  • Operating room planning
  • Pairwise interchange heuristics
  • Patient health condition
  • Sample average approximation
  • Scheduling

ASJC Scopus subject areas

  • Strategy and Management
  • Management Science and Operations Research
  • Information Systems and Management

Cite this

Scheduling elective surgery patients considering time-dependent health urgency : Modeling and solution approaches. / Eun, Joonyup; Kim, Sang Phil; Yih, Yuehwern; Tiwari, Vikram.

In: Omega (United Kingdom), Vol. 86, 01.07.2019, p. 137-153.

Research output: Contribution to journalArticle

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