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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Operations Research for Health Care

ISSN

2211-6923

e-ISSN

—

Svazek periodika

8

Číslo periodika v rámci svazku

March

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

9

Strana od-do

33-41

Kód UT WoS článku

000382002200005

EID výsledku v databázi Scopus

2-s2.0-84941255102