Abstract
We propose a multistage stochastic mixed-integer programming formulation for the assignment of surgeries to operating rooms over a finite planning horizon. We consider the demand for and the duration of surgery to be random variables. The objective is to minimize three competing criteria: expected cost of surgery cancellations, patient waiting time, and operating room overtime. We discuss properties of the model and an implementation of the progressive hedging algorithm to find near-optimal surgery schedules. We conduct numerical experiments using data from a large hospital to identify managerial insights related to surgery planning and the avoidance of surgery cancellations. We compare the progressive hedging algorithm to an easy-to-implement heuristic for practical problem instances to estimate the value of the stochastic solution. Finally, we discuss an implementation of the progressive hedging algorithm within a rolling horizon framework for extended planning periods.
Original language | English (US) |
---|---|
Pages (from-to) | 755-772 |
Number of pages | 18 |
Journal | INFORMS Journal on Computing |
Volume | 27 |
Issue number | 4 |
DOIs | |
State | Published - Sep 1 2015 |
Keywords
- Heuristics
- Progressive hedging
- Scheduling
- Stochastic programming
- Surgery planning
ASJC Scopus subject areas
- Software
- Information Systems
- Computer Science Applications
- Management Science and Operations Research