Variations of Double Coverage Ambulance Location Model Using Call Volume and Population Data

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Date

2019

Authors

Gizem Mullaoğlu
Gorkem Sariyer

Journal Title

Journal ISSN

Volume Title

Publisher

Taylor and Francis Ltd. michael.wagreich@univie.ac.at

Open Access Color

Green Open Access

Yes

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No
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Average
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Average
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Abstract

In Emergency Medical Services (EMS) ability to respond to emergency situations rapidly is very crucial. One of the main decisions that need to be made by the EMS provider is to locate available ambulances in an efficient way that all possible demand can be covered at a reasonable amount of time. For the ambulance location problem we propose three new optimization models employing Double Standard Model as a base. We make an elaborate analysis to decide on the minimum number of ambulances required in each location. Using real-life data from İzmir Turkey proposed optimization models are solved for both the population and the call volume data. Consequently this study mainly showed that in solving ambulance location problem the use of call volume data and preparing periodical plans are more efficient than using either population data or preparing plans based on daily call volume data. © 2020 Elsevier B.V. All rights reserved.

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Keywords

Ambulance Location, Double-coverage Models, Emergency Medical Services, Mathematical Modeling, Ambulances, Emergency Services, Location, Mathematical Models, Optimization, Coverage Models, Emergency Medical Services, Emergency Situation, Location Modeling, Location Problems, Optimization Models, Population Data, Standard Model, Population Statistics, Ambulances, Emergency services, Location, Mathematical models, Optimization, Coverage models, Emergency medical services, Emergency situation, Location modeling, Location problems, Optimization models, Population data, Standard model, Population statistics, Emergency Medical Services, Mathematical Modeling, Ambulance Location, Double-Coverage Models

Fields of Science

0211 other engineering and technologies, 02 engineering and technology

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OpenCitations Citation Count
2

Source

Journal of Industrial and Production Engineering

Volume

36

Issue

8

Start Page

533

End Page

545
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Scopus : 3

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Mendeley Readers : 17

SCOPUS™ Citations

3

checked on Apr 09, 2026

Web of Science™ Citations

1

checked on Apr 09, 2026

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0.5327

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