A two-level optimization model for elective surgery scheduling with downstream capacity constraints

DOI10.1016/j.ejor.2019.01.036zbMath1430.90305OpenAlexW2909737634WikidataQ128537383 ScholiaQ128537383MaRDI QIDQ666974

Jian Zhang, Abdellah El Moudni, Mahjoub Dridi

Publication date: 12 March 2019

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ejor.2019.01.036

zbMATH Keywords

Markov decision processapproximate dynamic programmingOR in health servicessurgery schedulingrecursive least-squares temporal difference learning

Mathematics Subject Classification ID

Stochastic scheduling theory in operations research (90B36) Markov and semi-Markov decision processes (90C40)

Related Items (10)

Current trends in operating room scheduling 2015 to 2020: a literature review ⋮ Surgical scheduling by fuzzy model considering inpatient beds shortage under uncertain surgery durations ⋮ An approximate dynamic programming approach to the admission control of elective patients ⋮ Stochastic optimization approaches for elective surgery scheduling with downstream capacity constraints: models, challenges, and opportunities ⋮ Data-driven distributionally robust surgery planning in flexible operating rooms over a Wasserstein ambiguity ⋮ Adopting a hierarchical diagnosis and treatment system to optimize elective surgery scheduling ⋮ Dynamic surgery management under uncertainty ⋮ Simulation-based rolling horizon scheduling for operating theatres ⋮ A distributionally robust optimization approach for stochastic elective surgery scheduling with limited intensive care unit capacity ⋮ Dynamic advance scheduling of outpatient appointments in a moving booking window

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