A comparison of formulations and solution methods for the minimum-envy location problem

Espejo, Inmaculada; Marı́n, Alfredo; Puerto, Justo; Rodríguez‐Chía, Antonio M.

doi:10.1016/j.cor.2008.06.013

Cited by 43 publications

(27 citation statements)

References 25 publications

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“…Espejo et al. () introduced the envy criteria, which measures the difference between pairs of customers (thus, is a measure of equity). Based on Espejo et al.…”

Section: Review Of Related Literaturementioning

confidence: 99%

“…Based on Espejo et al. (), Chanta et al. () proposed the minimum p ‐envy location model, relaxing the strict and ordinal preference assumptions made originally in Espejo et al.…”

Section: Review Of Related Literaturementioning

confidence: 99%

“…() proposed the minimum p ‐envy location model, relaxing the strict and ordinal preference assumptions made originally in Espejo et al. (), and including backup servers. Most of the equity considerations in location problems have been devoted to reducing disparities among customers, but they are not the only players in the system.…”

Section: Review Of Related Literaturementioning

confidence: 99%

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Identifying trade‐offs in equity and efficiency for simultaneously optimizing location and multipriority dispatch of ambulances

Enayati

Mayorga

Toro-Díaz

et al. 2018

Int Trans Operational Res

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The role of emergency medical service (EMS) systems is to provide acute care and possibly transportation to health care facilities to patients experiencing medical emergencies. Since EMS is a public service, it is natural for the community to expect equitable service from these systems; however, there is not a unique agreement on how to measure equity. Most EMS planning literature focuses solely on measures of efficiency, such as minimizing average response time. Solutions based on optimizing efficiency measures alone can be unacceptable when they are achieved at the expense of some players. Such trade‐offs can be more crucial when it comes to high‐priority emergencies. We provide a multicriteria optimization approach aimed at identifying good solutions for several equity and efficiency measures together, based on a joint modeling approach for location and dispatching policy decisions, while considering multiple levels of call priority. We apply our approach to a real‐world data set. We show that the joint approach provides better solutions than using the common assignment of the closest available ambulance, in particular for the equity criteria. We quantify the trade‐offs between different performance measures, and provide Pareto‐efficient solutions. The proposed joint optimization approach can be used to gain insight about the implicit balance between common efficiency measures and discussed equity criteria, hence providing better information to policy makers and EMS system administrators.

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“…Espejo et al. () introduced the envy criteria, which measures the difference between pairs of customers (thus, is a measure of equity). Based on Espejo et al.…”

Section: Review Of Related Literaturementioning

confidence: 99%

“…Based on Espejo et al. (), Chanta et al. () proposed the minimum p ‐envy location model, relaxing the strict and ordinal preference assumptions made originally in Espejo et al.…”

Section: Review Of Related Literaturementioning

confidence: 99%

Section: Review Of Related Literaturementioning

confidence: 99%

See 1 more Smart Citation

Identifying trade‐offs in equity and efficiency for simultaneously optimizing location and multipriority dispatch of ambulances

Enayati

Mayorga

Toro-Díaz

et al. 2018

Int Trans Operational Res

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“…Constraint (4) fixes the number of facilities to p . Constraints (5), as pointed out by Espejo et al (), permit to allocate each demand point to the closest facility. Constraints (6) and (7) indicate that variables are binary.…”

Section: The Formulation Of a P‐flp With Equality Objectivementioning

confidence: 99%

Exploring Similarities in Discrete Facility Location Models with Equality Measures

Barbati¹,

Bruno

2017

Geographical Analysis

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There have been a number of discrete facility location models that deal with the use of some equality measures of the distances between the facility and the users. They have been used to guarantee a similar level of equity among the users that may be affected in a positive or in a good way from a facility. These models have been formulated trying to adapt equality measures taken from contexts different from the location one. This way, every measure is very specific to the particular application and it is not highlighted why a measure should be selected and what is the contribution to the equity distribution among the users that can provide. In this article, we propose a facility location problem in which we have to locate a given number of facilities among a set of potential facilities, optimizing an equality measure. We propose a computational study to test the similarities and the differences of a good number of measures with more than a single facility to locate and we point out which measures produce similar results and how they depend on each other.

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“…The literature includes many works on this area related to combinatorial optimization. Some examples, among many others, include minimax problems (Hansen, 1980;Schrijver, 1983), combining minisum and minimax (Averbakh and Berman, 1995;Hansen and Labbé, 1988;Hansen et al, 1991;Minoux, 1989;Punnen et al, 1995;Tamir et al, 2002), k-centrum optimization (Garfinkel et al, 2006;Kalcsics et al, 2002;Punnen, 1992;Slater, 1978a,b;Tamir, 2000), lexicographic optimization (Calvete and Mateo, 1998;Croce et al, 1999), k-th best solutions (Lawler, 1972;Martello et al, 1984;Pascoal et al, 2003;Yen, 1971), most uniform solutions (Galil and Schieber, 1998;López de los Mozos et al, 2008), minimumenvy solutions (Espejo et al, 2009), solutions with minimum deviation (Gupta et al, 1990), regret solutions (Averbakh, 2001;Conde, 2004;Puerto and Rodríguez-Chía, 2003), equity measures (Gupta and Punnen, 1988;López de los Mozos et al, 2008;Mesa et al, 2003;Punnen and Aneja, 1997), discrete ordered median location problems (Boland et al, 2006;Marín et al, 2009;Puerto, 2008;Puerto and Tamir, 2005;Puerto and Rodríguez-Chía, 2015), ordered weighted average objectives (Fernández et al, 2013(Fernández et al, , 2014Galand and Spanjaard, 2012), and covering objectives …”

Section: Introductionmentioning

confidence: 99%

Ordered Weighted Average optimization in Multiobjective Spanning Tree Problem

Fernández

Pozo

Puerto

et al. 2017

European Journal of Operational Research

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A comparison of formulations and solution methods for the minimum-envy location problem

Cited by 43 publications

References 25 publications

Identifying trade‐offs in equity and efficiency for simultaneously optimizing location and multipriority dispatch of ambulances

Identifying trade‐offs in equity and efficiency for simultaneously optimizing location and multipriority dispatch of ambulances

Exploring Similarities in Discrete Facility Location Models with Equality Measures

Ordered Weighted Average optimization in Multiobjective Spanning Tree Problem

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