Paper Info
Title
A Two-Stage Stochastic Integer Programming Approach to Integrated Staffing and Scheduling with Application to Nurse Management
Abstract
AbstractWe study the problem of integrated staffing and scheduling under demand uncertainty. This problem is formulated as a two-stage stochastic integer program with mixed-integer recourse. The here-and-now decision is to find initial staffing levels and schedules. The wait-and-see decision is to adjust these schedules at a time closer to the actual date of demand realization. We show that the mixed-integer rounding inequalities for the second-stage problem convexify the recourse function. As a result, we present a tight formulation that describes the convex hull of feasible solutions in the second stage. We develop a modified multicut approach in an integer L-shaped algorithm with a prioritized branching strategy. We generate 20 instances each with more than 1.3 million integer and 4 billion continuous variables of the staffing and scheduling problem using 3.5 years of patient volume data from Northwestern Memorial Hospital. Computational results show that the efficiency gained from the convexification of the recourse function is further enhanced by our modifications to the L-shaped method. The results also show that compared with a deterministic model, the two-stage stochastic model leads to a significant cost savings. The cost savings increase with mean absolute percentage errors in the patient volume forecast.
Year
DOI
Venue
2015
10.1287/opre.2015.1421
Periodicals
Keywords
Field
DocType
stochastic programming,hospitals,personnel scheduling
Mathematical optimization,Job shop scheduling,Staffing,Scheduling (computing),Computer science,Rounding,Schedule,Deterministic system,Stochastic modelling,Stochastic programming,Operations management
Journal
Volume
Issue
ISSN
63
6
0030-364X
Citations 
PageRank 
References 
12
0.56
32
Authors
2
Name
Order
Citations
PageRank
kibaek kim1202.19
Sanjay Mehrotra252177.18