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A Bi-objective Covering Location Problem: Case of ambulance location in the Beirut area, Lebanon

Bilal El Itani (Department of Information Systems, NEOMA Business School, Mont-Saint-Aignan, France)
Fouad Ben Abdelaziz (Department of Information Systems, NEOMA Business School, Mont-Saint-Aignan, France)
Hatem Masri (Department of Management and Marketing, College of Business Administration, University of Bahrain, Sakhir, Bahrain)

Management Decision

ISSN: 0025-1747

Article publication date: 5 October 2018

Issue publication date: 26 February 2019

419

Abstract

Purpose

Ambulance response time is an important factor in saving lives and is highly linked with the ambulance location problem. The Maximum Expected Covering Location Problem (MEXCLP), introduced by Daskin (1983), is one of the most used ambulance location models that maximize the probability of stratifying demands for emergency medical service (EMS) centers. Due to huge increase in the operational costs of EMS centers, ambulance location models must consider the cost of coverage and the opportunity to use other companies’ private ambulances to answer emergency calls. The paper aims to discuss these issues.

Design/methodology/approach

In this paper, the authors propose to extend the MEXCLP to a bi-objective optimization problem where the cost of satisfying emergency calls is minimized.

Findings

The proposed model is tested using data retrieved from the Lebanese Red Cross (LRC) in Beirut capital of Lebanon. The reported findings show significant enhancements in the results where the LRC can fully satisfy the perceived demands from all areas in Beirut within 9 min with an affordable cost.

Originality/value

The model is a first attempt to reduce operational costs of EMS centers while constraining the response time to satisfy emergency calls at an acceptable rate.

Keywords

Citation

El Itani, B., Ben Abdelaziz, F. and Masri, H. (2019), "A Bi-objective Covering Location Problem: Case of ambulance location in the Beirut area, Lebanon", Management Decision, Vol. 57 No. 2, pp. 432-444. https://doi.org/10.1108/MD-04-2018-0474

Publisher

:

Emerald Publishing Limited

Copyright © 2018, Emerald Publishing Limited

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