Comparison of static ambulance location models

Pieter L. Van Den Berg and J. Theresia Van Essen

International Journal of Logistics Systems and Management, 2019, vol. 32, issue 3/4, 292-321

Abstract: Over the years, several ambulance location models have been discussed in the literature. Most of these models have been further developed to take more complicated situations into account. However, the existing standard models that are often used in case studies have never been compared computationally according to the criteria used in practice. In this paper, we compare several ambulance location models on coverage and response time criteria. In addition to four standard ambulance location models from the literature, we also present two models that focus on average and expected response times. The computational results show that the maximum expected covering location problem (MEXCLP) and the expected response time model (ERTM) perform the best over all considered criteria. However, as the computation times for ERTM are long, the average response time model (ARTM) could be a good alternative. Based on these results, we also propose four alternative models that combine the good coverage provided by MEXCLP and the quick response times provided by ARTM. All four considered models provide balanced solutions in terms of coverage and response times. However, the multiple response times target model (MRTTM) outperforms the other models based on computation time.

Keywords: emergency medical services; integer linear programming; ambulance base locations; comparative study. (search for similar items in EconPapers)
Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
http://www.inderscience.com/link.php?id=98321 (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:ids:ijlsma:v:32:y:2019:i:3/4:p:292-321

Access Statistics for this article

More articles in International Journal of Logistics Systems and Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().