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Authors: Ryota Akiyama ; Mari Ito and Ryuta Takashimaand Kinju Hoshino

Affiliation: Department of Industrial Administration Faculty of Science and Technology, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba 278-8510, Japan

Keyword(s): Stochastic Programming, Emergency Surgery, Surgery Planning, Operating Room.

Abstract: This paper introduces a stochastic programming model for a hospital with two surgery types: elective and emergency surgeries. We propose a model that decides the number of the elective surgeries per day according to a scheme that makes best use of the operating rooms. Specifically, we model when the demand capacity for emergency surgery in the operating room of one day is uncertain. We created multiple surgery times, performed random sampling, and conducted numerical experiments. In the results, emergency surgery changed the allocation of elective surgery. In this paper, we report on the proposed model and numerical results, and discuss these and the future research prospects.

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Paper citation in several formats:
Akiyama, R.; Ito, M. and Hoshino, R. (2022). Stochastic Programming Model for Elective Surgery Planning: An Effect of Emergency Surgery. In Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - ICORES; ISBN 978-989-758-548-7; ISSN 2184-4372, SciTePress, pages 231-235. DOI: 10.5220/0010901800003117

@conference{icores22,
author={Ryota Akiyama. and Mari Ito. and Ryuta Takashimaand Kinju Hoshino.},
title={Stochastic Programming Model for Elective Surgery Planning: An Effect of Emergency Surgery},
booktitle={Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - ICORES},
year={2022},
pages={231-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010901800003117},
isbn={978-989-758-548-7},
issn={2184-4372},
}

TY - CONF

JO - Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - ICORES
TI - Stochastic Programming Model for Elective Surgery Planning: An Effect of Emergency Surgery
SN - 978-989-758-548-7
IS - 2184-4372
AU - Akiyama, R.
AU - Ito, M.
AU - Hoshino, R.
PY - 2022
SP - 231
EP - 235
DO - 10.5220/0010901800003117
PB - SciTePress

- Science and Technology Publications, Lda.
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