Linear formulation for the Maximum Expected Coverage Location Model with fractional coverage

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F16%3A10384630" target="_blank" >RIV/00216208:11320/16:10384630 - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1016/j.orhc.2015.08.001" target="_blank" >https://doi.org/10.1016/j.orhc.2015.08.001</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.orhc.2015.08.001" target="_blank" >10.1016/j.orhc.2015.08.001</a>

Result language

angličtina

Original language name

Linear formulation for the Maximum Expected Coverage Location Model with fractional coverage

Original language description

Since ambulance providers are responsible for life-saving medical care at the scene in emergency situations and since response times are important in these situations, it is crucial that ambulances are located in such a way that good coverage is provided throughout the region. Most models that are developed to determine good base locations assume strict 0-1 coverage given a fixed base location and demand point. However, multiple applications require fractional coverage. Examples include stochastic, instead of fixed, response times and survival probabilities. Straightforward adaption of the well-studied MEXCLP to allow for coverage probabilities results in a non-linear formulation in integer variables, limiting the size of instances that can be solved by the model. In this paper, we present a linear integer programming formulation for the problem. We show that the computation time of the linear formulation is significantly shorter than that for the non-linear formulation. As a consequence, we are able to solve larger instances. Finally, we will apply the model, in the setting of stochastic response times, to the region of Amsterdam, the Netherlands.

Czech name

—

Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

10103 - Statistics and probability

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2016

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Operations Research for Health Care

ISSN

2211-6923

e-ISSN

—

Volume of the periodical

8

Issue of the periodical within the volume

March

Country of publishing house

GB - UNITED KINGDOM

Number of pages

9

Pages from-to

33-41

UT code for WoS article

000382002200005

EID of the result in the Scopus database

2-s2.0-84941255102