A Sequential Follower Refinement Algorithm for Robust Surgery Scheduling

Ankit Bansal (), Jean-Philippe Richard (), Bjorn P. Berg () and Yu-Li Huang ()
Additional contact information
Ankit Bansal: Department of Systems Science and Industrial Engineering, State University of New York, Binghamton, New York 13902
Jean-Philippe Richard: Department of Industrial and Systems Engineering, University of Minnesota, Minneapolis, Minnesota 55455
Bjorn P. Berg: Division of Health Policy and Management, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455
Yu-Li Huang: Robert D. and Patricia E. Kern Center for the Science of Healthcare Delivery, Mayo Clinic, Rochester, Minnesota 55905

INFORMS Journal on Computing, 2024, vol. 36, issue 3, 918-937

Abstract: An algorithm for the two-stage robust optimization surgery-to-operating room allocation problem is presented. The second-stage problem is an integer linear program whose convex hull is approximated using three types of specialized valid inequalities and Chvátal-Gomory cuts. The resulting linear relaxation of the second-stage problem is then dualized and integrated into the first-stage problem. The resulting mixed integer linear program, which is an approximation of the original problem, is then solved using a commercial solver. If the solution of this model is not optimal for the second-stage problem, valid inequalities for the second-stage problem are generated, yielding a type of column-generation based approach that we refer to as the sequential follower refinement ( SFR ) algorithm. Data from an academic medical center are used to compare the computational performance of SFR with the constraint and column generation ( C&CG ) algorithm, which is the only exact approach that has been specifically applied for this problem in the literature. An extensive numerical study of SFR and its computational characteristics is presented that shows that SFR yields better-quality solutions compared with C&CG , even as the termination criterion of SFR is met much sooner, especially for problems involving higher number of surgeries.

Keywords: robust optimization; surgery scheduling; column generation; convex hull approximation; Chvátal-Gomory cuts (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://dx.doi.org/10.1287/ijoc.2022.0191 (application/pdf)

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:inm:orijoc:v:36:y:2024:i:3:p:918-937

Access Statistics for this article

More articles in INFORMS Journal on Computing from INFORMS Contact information at EDIRC.
Bibliographic data for series maintained by Chris Asher ().