Distributionally robust scheduling of stochastic knapsack arrivals

Hayo Bos*, Richard J. Boucherie, Erwin W. Hans, Gréanne Leeftink

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)
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Abstract

This paper studies the discrete-time Stochastic Knapsack with Periodic Scheduled Arrivals (SKPSA). The goal is to find a schedule such that the capacity usage of the unconstrained cousin of the knapsack is as close as possible to a target utilization. We approximate the SKPSA with a Wasserstein distance based Distributionally Robust Optimization (DRO) model, resulting in the DRO-SKPSA. We present an algorithm that efficiently solves this model, and show that the DRO-SKPSA produces robust schedules. The problem arises in particular in healthcare settings in the development of Master Surgical Schedules (MSSs). We discuss managerial insights for MSSs with downstream capacity constraints.

Original languageEnglish
Article number106641
JournalComputers and Operations Research
Volume167
Early online date2 Apr 2024
DOIs
Publication statusPublished - Jul 2024

Keywords

  • UT-Hybrid-D
  • Distributionally robust optimization
  • Master surgical schedule
  • Scheduled arrivals
  • Stochastic knapsack
  • Wasserstein distance
  • Cyclic schedule

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