- -

A mixed integer linear program for a real relocation problem of emergency medical vehicles in the province of Valencia

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

A mixed integer linear program for a real relocation problem of emergency medical vehicles in the province of Valencia

Mostrar el registro sencillo del ítem

Ficheros en el ítem

Thumbnail
Nombre: VecinaVillaVallada ...
Tamaño: 2.055Mb
Formato: PDF
Descripción: Versión editorial
Abrir
dc.contributor.author Vecina García, Miguel Ángel es_ES
dc.contributor.author Villa Juliá, María Fulgencia es_ES
dc.contributor.author Vallada Regalado, Eva es_ES
dc.contributor.author Karpova Krylova, Yulia es_ES
dc.coverage.spatial east=-0.7532808999999999; north=39.4840108; name=Provincia de Valencia, Espanya es_ES
dc.date.accessioned 2022-09-05T09:45:17Z
dc.date.available 2022-09-05T09:45:17Z
dc.date.issued 2022-07-29
dc.identifier.uri http://hdl.handle.net/10251/185192
dc.description.abstract [EN] The rapid intervention of Advanced Life Support (ALS) and Basic Life Support (BLS) when an emergency arises is of vital importance for the welfare of citizens. Currently, these Emergency Medical Vehicles (EMV) are located, in the province of Valencia, in certain logistical bases according to the criteria of those responsible for the Emergency Medical Services (EMS). However, it is not possible to cover the entire population of the province within the stipulated maximum times of 12 and 15 minutes (depending on whether it is an ALS or BLS, respectively). For this reason, a maximum coverage model is used to relocate the EMV bases in order to minimize the amount of uncovered population in the province. Thanks to the proposed model, the total coverage defect of the province's population is reduced by more than half compared to the current distribution. es_ES
dc.description.sponsorship This work is part of the project submitted to the Valencian Innovation Agency (AVI) in the 2021 call entitled iREVES (innovación en Reubicación de Vehículos de Emergencias Sanitarias): an intelligent decision-making tool. Part of the authors are supported by the Faculty of Business Administration and Management at Universitat Politècnica de València. This work is part of a Bachelor’s Degree Final Project awarded with a mention in Missions València 2030 and the second prize of CEMEX at Universitat Politècnica de València. Mention should also be made to all those responsible for the EMS from Comunitat Valenciana for providing all the necessary information and being willing to offer their help at all times. es_ES
dc.language Inglés es_ES
dc.publisher Universitat Politècnica de València es_ES
dc.relation.ispartof Journal of Applied Research in Technology & Engineering es_ES
dc.rights Reconocimiento - No comercial - Compartir igual (by-nc-sa) es_ES
dc.subject Location es_ES
dc.subject Isochrone es_ES
dc.subject Optimization es_ES
dc.subject Emergencies es_ES
dc.subject Mathematical model es_ES
dc.title A mixed integer linear program for a real relocation problem of emergency medical vehicles in the province of Valencia es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.4995/jarte.2022.16984
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario Mixto de Tecnología de Informática - Institut Universitari Mixt de Tecnologia d'Informàtica es_ES
dc.contributor.affiliation Universitat Politècnica de València. Facultad de Administración y Dirección de Empresas - Facultat d'Administració i Direcció d'Empreses es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Vecina García, MÁ.; Villa Juliá, MF.; Vallada Regalado, E.; Karpova Krylova, Y. (2022). A mixed integer linear program for a real relocation problem of emergency medical vehicles in the province of Valencia. Journal of Applied Research in Technology & Engineering. 3(2):85-92. https://doi.org/10.4995/jarte.2022.16984 es_ES
dc.description.accrualMethod OJS es_ES
dc.relation.publisherversion https://doi.org/10.4995/jarte.2022.16984 es_ES
dc.description.upvformatpinicio 85 es_ES
dc.description.upvformatpfin 92 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 3 es_ES
dc.description.issue 2 es_ES
dc.identifier.eissn 2695-8821
dc.relation.pasarela OJS\16984 es_ES
dc.description.references Bélanger, V., Ruiz, Á., & Soriano, P. (2015). Recent Advances in Emergency Medical Services Management. (L. a. Interuniversity Research Centre on Enterprise Networks, Ed.) Montréal, Canada: CIRRELT. es_ES
dc.description.references Brotcorne, L., Laporte, G., & Semet, F. (2003, June 16). Ambulance location and relocation models. European Journal of Operational Research, 147(3), 451-463. https://doi.org/10.1016/S0377-2217(02)00364-8 es_ES
dc.description.references Cheu, R.L., Huang, Y., & Huang, B. (2008). Allocating Emergency Service Vehicles to Serve Critical Transportation Infrastructures. Journal of Intelligent Transportation Systems Technology Planning and Operations, 12(1), 38-49. https://doi.org/10.1080/15472450701849675 es_ES
dc.description.references Dorigo, M., Birattari, M., & Stutzle, T. (2006). Ant colony optimization. IEEE Computational Intelligence Magazine, 1(4), 28-39. https://doi.org/10.1109/MCI.2006.329691 es_ES
dc.description.references Erkut, E., Ingolfsson, A., & Erdogan, G. (2008, February). Ambulance location for maximum survival. Naval Research Logistics, 55(1), 42-58. https://doi.org/10.1002/nav.20267 es_ES
dc.description.references Gendreau, M., Laporte, G., & Semet, F. (August de 1997). Solving an ambulance location model by tabu search. ScienceDirect, 5(2), 75-88. https://doi.org/10.1016/S0966-8349(97)00015-6 es_ES
dc.description.references Geroliminis, N.G. Karlaftis, M., & Skabardonis, A. (2009). A spatial queuing model for the emergency vehicle districting and location problem. Transportation Research Part B Methodological, 43(7), 798-811. https://doi.org/10.1016/j.trb.2009.01.006 es_ES
dc.description.references Hsia, H.-C., Ishii, H., & Yeh, K.-Y. (2009). Ambulance service facility location problem. Journal of the Operations Research, 52(3), 339-354. https://doi.org/10.15807/jorsj.52.339 es_ES
dc.description.references Ingolfsson, A., Budge, S., & Erkut, E. (2008). Optimal Ambulance Location with Random Delays and Travel Times. Health Care Management Science, 11(3), 262-274. https://doi.org/10.1007/s10729-007-9048-1 es_ES
dc.description.references Marianov, V., & ReVelle, C. (1996). The Queueing Maximal availability location problem: A model for the siting of emergency vehicles. European Journal of Operational Research, 93(1), 110-120. https://doi.org/10.1016/0377-2217(95)00182-4 es_ES
dc.description.references ReVelle, C. (1989). Review, extension and prediction in emergency service siting models. European Journal of Operational Research, 40(1), 58-69. https://doi.org/10.1016/0377-2217(89)90272-5 es_ES
dc.description.references Shariat-Mohaymany, A., Babaei, M., Moadi, S., & Mahdi Amiripour, S. (2012). Linear upper-bound unavailability set covering models for locating ambulances: Application to Tehran rural roads. European Journal of Operational Research, 221(1), 263-272. https://doi.org/10.1016/j.ejor.2012.03.015 es_ES
dc.description.references Su, Q., Luo, Q., & Huang, S. (2015). Cost-effective analyses for emergency medical services deployment: A case study in Shanghai. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2015.02.015 es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem