A multi-period emergency medical service location problem based on Wasserstein-metric approach using generalised benders decomposition method

Yuefei Yuan, Qiankun Song and Bo Zhou

International Journal of Systems Science, 2023, vol. 54, issue 6, 1173-1185

Abstract: This paper considers a multi-period location and sizing problem for an emergency medical service (EMS) system based on a distributionally robust optimisation (DRO) chance-constrained programming approach. The dynamic uncertain emergency medical requests are described in the ambiguity set, which is constructed based on Wasserstein-metric. The model of this problem focuses on minimising long-term operation costs. The chance constraints ensure the reliability of EMS system for the entire geographic areas. A reformulation of chance constraints is provided in Mixed Integer Linear Program form. For problem solution, a generalised Benders decomposition (GBD) implementation is proposed. A numerical simulation is conducted to illustrate the performance of two solution approaches in terms of computational convergence speed and optimality of the problem.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/00207721.2023.2168144 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tsysxx:v:54:y:2023:i:6:p:1173-1185

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TSYS20

DOI: 10.1080/00207721.2023.2168144

Access Statistics for this article

International Journal of Systems Science is currently edited by Visakan Kadirkamanathan

More articles in International Journal of Systems Science from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().