Stochastic Programming Model for Elective Surgery Planning: An Effect of Emergency Surgery

Ryota Akiyama, Mari Ito, Ryuta Hoshino

2022

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.

Paper Citation

in Harvard Style

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 - Volume 1: ICORES, ISBN 978-989-758-548-7, pages 231-235. DOI: 10.5220/0010901800003117

in Bibtex Style

@conference{icores22,
author={Ryota Akiyama and Mari Ito and Ryuta 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 - Volume 1: ICORES,},
year={2022},
pages={231-235},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0010901800003117},
isbn={978-989-758-548-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 11th International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Stochastic Programming Model for Elective Surgery Planning: An Effect of Emergency Surgery
SN - 978-989-758-548-7
AU - Akiyama R.
AU - Ito M.
AU - Hoshino R.
PY - 2022
SP - 231
EP - 235
DO - 10.5220/0010901800003117