Open Access Open Access  Restricted Access Subscription or Fee Access

A mathematical model for efficient ambulance location based on DSM-MALP integration

Mehdi Nasr Isfahani, MD, Mohammad Ali Rafieian, MSc, Aniseh Valikhany, MD, Mehdi Alinaghian, PhD

Abstract


Optimal location of medical facilities and vehicles is one of the most crucial aspects of emergency services such that even slight improvements in this regard can save the lives of many people. In the large cities suffering from fluctuating population distribution and traffic congestion, finding the optimal location of ambulance stations can significantly reduce patient mortality due to delay of medical service and thus increase the efficiency of the healthcare sector. This study investigated the current status of ambulance service provided in four districts of Isfahan city (Iran) and assessed the potential for improvement in availability by increasing the number of ambulances and relocating the stations. The main objective of this work is to integrate two ambulance location methods, ie, double standard model (DSM) and maximum availability location problem (MALP), to develop a static probabilistic model, which allows covering radius of stations to be increased according to ambulance availability factor. The efficiency of the developed method was assessed by sensitivity analysis through four different approaches, all indicating an increase in the efficiency compared to the default model.


Keywords


double standard model, maximum availability location problem, ambulance location, emergency medical services

Full Text:

PDF

References


Davari F, Nasr Isfahani M, RezvaniMajid, et al: Process management model in the emergency department of a university hospital: Reduction of patient waiting times by changes in human resources. J Res Med Dent Sci. 2018; 6(2): 578-585.

Arabani AB, Farahani RZ: Facility location dynamics: An overview of classifications and applications. Comput Ind Eng. 2012; 62(1): 408-420.

Sepehri M, Maleki M, Majlesi Nasab N: Relocation of deployed ambulances. Int J Ind Eng Prod Manage. 2013; 2: 172-182.

Anbari E, Yarmohammadian MH, Nasr Isfahani M: From investigation of hospital protocols and guidelines to designing a generic protocol for responding to chemical, biological, radiological, and nuclear incidents. Int J Health Syst Disaster Manage. 2015; 3(4): 195-199.

Rajagopalan HK, Saydam C, Xiao J: A multiperiod set covering location model for dynamic redeployment of ambulances. Comput Oper Res. 2008; 35(3): 814-826.

Yang X, Lo C: Modelling urban growth and landscape changes in the Atlanta metropolitan area. Int J Geogr Inf Sci. 2003; 17(5): 463-488.

Lotfi S, Koohsari MJ: Measuring objective accessibility to neighborhood facilities in the city (A case study: Zone 6 in Tehran, Iran). Cities. 2009; 26(3): 133-140.

Owen SH, Daskin MS: Strategic facility location: A review. Eur J Oper Res. 1998; 111(3): 423-447.

Averbakh I, Berman O: Minimax regret p-center location on a network with demand uncertainty. Locat Sci. 1997; 5(4): 247-254.

Toregas C, Swain R, ReVelle C, et al.: The location of emergency service facilities. Oper Res. 1971; 19(6): 1363-1373.

Church R, ReVelle C: The maximal covering location problem. Pap Reg Sci Assoc. 1974; 32(1): 101-118.

Schilling D, Elzinga DJ, Cohon J, et al.: The TEAM/FLEET models for simultaneous facility and equipment siting. Transport Sci. 1979; 13(2): 163-175.

ReVelle C, Hogan K: The maximum availability location problem. Transport Sci. 1989; 23(3): 192-200.

Gendreau M, Laporte G, Semet F: Solving an ambulance location model by tabu search. Locat Sci. 1997; 5(2): 75-88.

Daskin MS: A maximum expected covering location model: Formulation, properties and heuristic solution. Transportation sci. 1983; 17(1): 48-70.

Ball MO, Lin FL: A reliability model applied to emergency service vehicle location. Oper Res. 1993; 41(1): 18-36.

Marianov V, Revelle C: The queuing probabilistic location set covering problem and some extensions. Locat Sci. 1996; 4(4): 277.

Kolesar P, Walker WE: An algorithm for the dynamic relocation of fire companies. Oper Res. 1974; 22(2): 249-274.

Gendreau M, Laporte G, Semet F: A dynamic model and parallel tabu search heuristic for real-time ambulance relocation. Parallel Comput. 2001; 27(12): 1641-1653.

Schmid V, Doerner KF: Ambulance location and relocation problems with time-dependent travel times. Eur J Oper Res. 2010; 207(3): 1293-1303.

Maxwell MS, Ni EC, Tong C, et al.: A bound on the performance of an optimal ambulance redeployment policy. Oper Res. 2014; 62(5): 1014-1027.




DOI: https://doi.org/10.5055/jem.2020.0458

Refbacks

  • There are currently no refbacks.


Copyright (c) 2020 Journal of Emergency Management