A comparison of multi-objective spatial dispersion models for managing critical assets in urban areas

Paul J. Maliszewski, Michael Kuby, Mark W. Horner

Research output: Contribution to journalArticle

17 Citations (Scopus)

Abstract

A diverse array of spatial optimization models dealing with protection, service, coverage, equity, and risk can potentially aid with the effective placement of critical assets. Protection of assets can be enhanced using the . p-dispersion model, which locates facilities to maximize the minimum distance between any two. Dispersion, however, is rarely the only objective for a system of facilities, and the . p-dispersion model is known to be difficult to solve. Therefore, this paper analyzes the trade-offs and computational times of four multi-objective models that combine the . p-dispersion model with other facility location objectives relevant to siting critical assets, such as the . p-median, max-cover, . p-center, and . p-maxian models. The multi-objective models are tested on a case study of Orlando, Florida. The dispersion/center model produced the most gradual trade-off curve, while the dispersion/maxian trade-off curve had the most pronounced " elbow." The center and median multi-objective models were far more computationally demanding than the models using max cover and . p-maxian. These findings may inform decision-makers and researchers in deciding what type of multi-objective models to use for planning dispersed networks of critical assets.

Original languageEnglish (US)
Pages (from-to)331-341
Number of pages11
JournalComputers, Environment and Urban Systems
Volume36
Issue number4
DOIs
StatePublished - Jul 2012

Fingerprint

assets
urban area
trade-off
p-median
comparison
facility location
optimization model
decision maker
equity
coverage
planning

Keywords

  • Critical infrastructure protection
  • Dispersion
  • Facility location

ASJC Scopus subject areas

  • Ecological Modeling
  • Environmental Science(all)
  • Geography, Planning and Development

Cite this

A comparison of multi-objective spatial dispersion models for managing critical assets in urban areas. / Maliszewski, Paul J.; Kuby, Michael; Horner, Mark W.

In: Computers, Environment and Urban Systems, Vol. 36, No. 4, 07.2012, p. 331-341.

Research output: Contribution to journalArticle

@article{e7c2b9dbf82147dc8ba0e8486d811e4d,
title = "A comparison of multi-objective spatial dispersion models for managing critical assets in urban areas",
abstract = "A diverse array of spatial optimization models dealing with protection, service, coverage, equity, and risk can potentially aid with the effective placement of critical assets. Protection of assets can be enhanced using the . p-dispersion model, which locates facilities to maximize the minimum distance between any two. Dispersion, however, is rarely the only objective for a system of facilities, and the . p-dispersion model is known to be difficult to solve. Therefore, this paper analyzes the trade-offs and computational times of four multi-objective models that combine the . p-dispersion model with other facility location objectives relevant to siting critical assets, such as the . p-median, max-cover, . p-center, and . p-maxian models. The multi-objective models are tested on a case study of Orlando, Florida. The dispersion/center model produced the most gradual trade-off curve, while the dispersion/maxian trade-off curve had the most pronounced {"} elbow.{"} The center and median multi-objective models were far more computationally demanding than the models using max cover and . p-maxian. These findings may inform decision-makers and researchers in deciding what type of multi-objective models to use for planning dispersed networks of critical assets.",
keywords = "Critical infrastructure protection, Dispersion, Facility location",
author = "Maliszewski, {Paul J.} and Michael Kuby and Horner, {Mark W.}",
year = "2012",
month = "7",
doi = "10.1016/j.compenvurbsys.2011.12.006",
language = "English (US)",
volume = "36",
pages = "331--341",
journal = "Computers, Environment and Urban Systems",
issn = "0198-9715",
publisher = "Elsevier Limited",
number = "4",

}

TY - JOUR

T1 - A comparison of multi-objective spatial dispersion models for managing critical assets in urban areas

AU - Maliszewski, Paul J.

AU - Kuby, Michael

AU - Horner, Mark W.

PY - 2012/7

Y1 - 2012/7

N2 - A diverse array of spatial optimization models dealing with protection, service, coverage, equity, and risk can potentially aid with the effective placement of critical assets. Protection of assets can be enhanced using the . p-dispersion model, which locates facilities to maximize the minimum distance between any two. Dispersion, however, is rarely the only objective for a system of facilities, and the . p-dispersion model is known to be difficult to solve. Therefore, this paper analyzes the trade-offs and computational times of four multi-objective models that combine the . p-dispersion model with other facility location objectives relevant to siting critical assets, such as the . p-median, max-cover, . p-center, and . p-maxian models. The multi-objective models are tested on a case study of Orlando, Florida. The dispersion/center model produced the most gradual trade-off curve, while the dispersion/maxian trade-off curve had the most pronounced " elbow." The center and median multi-objective models were far more computationally demanding than the models using max cover and . p-maxian. These findings may inform decision-makers and researchers in deciding what type of multi-objective models to use for planning dispersed networks of critical assets.

AB - A diverse array of spatial optimization models dealing with protection, service, coverage, equity, and risk can potentially aid with the effective placement of critical assets. Protection of assets can be enhanced using the . p-dispersion model, which locates facilities to maximize the minimum distance between any two. Dispersion, however, is rarely the only objective for a system of facilities, and the . p-dispersion model is known to be difficult to solve. Therefore, this paper analyzes the trade-offs and computational times of four multi-objective models that combine the . p-dispersion model with other facility location objectives relevant to siting critical assets, such as the . p-median, max-cover, . p-center, and . p-maxian models. The multi-objective models are tested on a case study of Orlando, Florida. The dispersion/center model produced the most gradual trade-off curve, while the dispersion/maxian trade-off curve had the most pronounced " elbow." The center and median multi-objective models were far more computationally demanding than the models using max cover and . p-maxian. These findings may inform decision-makers and researchers in deciding what type of multi-objective models to use for planning dispersed networks of critical assets.

KW - Critical infrastructure protection

KW - Dispersion

KW - Facility location

UR - http://www.scopus.com/inward/record.url?scp=84861221479&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84861221479&partnerID=8YFLogxK

U2 - 10.1016/j.compenvurbsys.2011.12.006

DO - 10.1016/j.compenvurbsys.2011.12.006

M3 - Article

AN - SCOPUS:84861221479

VL - 36

SP - 331

EP - 341

JO - Computers, Environment and Urban Systems

JF - Computers, Environment and Urban Systems

SN - 0198-9715

IS - 4

ER -