Objectives in Location Problems

Eiselt, H. A.; Laporte, Gilbert

doi:10.1007/978-1-4612-5355-6_9

Cited by 95 publications

(50 citation statements)

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“…The classical location theory is dedicated to the problem of locating a new facility such that all relevant distances, e.g. to customers, are minimized [7,8,11,13,19,35,42]. Nevertheless, since some facilities also cause negative effects like noise, stench or even danger, such facilities need to be established as far away as possible from nature reserves and residential areas.…”

Section: Application and Numerical Resultsmentioning

confidence: 99%

Solving DC programs with a polyhedral component utilizing a multiple objective linear programming solver

Löhne¹,

Wagner²

2017

J Glob Optim

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A class of non-convex optimization problems with DC objective function is studied, where DC stands for being representable as the difference f = g − h of two convex functions g and h. In particular, we deal with the special case where one of the two convex functions g or h is polyhedral. In case g is polyhedral, we show that a solution of the DC program can be obtained from a solution of an associated polyhedral projection problem. In case h is polyhedral, we prove that a solution of the DC program can be obtained by solving a polyhedral projection problem and finitely many convex programs. Since polyhedral projection is equivalent to multiple objective linear programming (MOLP), a MOLP solver (in the second case together with a convex programming solver) can be used to solve instances of DC programs with polyhedral component. Numerical examples are provided, among them an application to locational analysis.

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Section: Application and Numerical Resultsmentioning

confidence: 99%

Solving DC programs with a polyhedral component utilizing a multiple objective linear programming solver

Löhne¹,

Wagner²

2017

J Glob Optim

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“…In the mid 1970s, it seems that the topic of obnoxious location problem was represented by some researchers such as Goldman and also Church and Granfinkel for the first time (Eiselt and Laporte 1995). Maybe we can assume that after coming up of this topic in multi-objective problems, the MCDM techniques were started to be used to solve the MCDM problems.…”

Section: Modelsmentioning

confidence: 97%

Demand Point Aggregation Analaysis for Location Models

Sadigh

Fallah

2009

Facility Location

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“…In a disaster relief environment and broadly in the public sector, the literature focuses on social welfare through equity-based objectives by minimizing the variability of the distribution of distances (Eiselt andLaporte 1995, Erkut 1993). Dekle et al (2005) model an analogous location problem for Florida county disaster recovery centers as a set-covering problem, and use a two-stage approach to minimize the total number of centers.…”

Section: Related Literaturementioning

confidence: 99%

Casualty Collection Points Optimization: A Study for the District of Columbia

2015

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A casualty collection point (CCP) is a single, predetermined location that is organized, staffed, and equipped to provide decontamination (if required), emergency medical assessment, treatment, and, where necessary, onward transportation of victims of a mass casualty incident. Emergency planners in the District of Columbia have recognized the desirability of developing a tool to assist planners in selecting CCPs within the affected area following a major incident. We develop a CCP optimization model (CCPOM) that provides planners and policymakers with strategic and operational insights into the complex problem of selecting optimal CCP locations to maximize casualty throughput for a range of incident parameters. Even more relevant, the CCPOM determines the utilization of personnel, decontamination units, and ambulances, providing planners with a general structure for resource allocation and signaling shortfalls that may lead to bottlenecks in casualty processing at the CCPs. District planners found many nonintuitive CCPOM results to be significant to their planning, programming, and budgeting efforts, and now consider the model's categorized resource utilization to be an integral part in updating District plans for both national special security event planning and everyday events.

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Objectives in Location Problems

Cited by 95 publications

References 0 publications

Solving DC programs with a polyhedral component utilizing a multiple objective linear programming solver

Solving DC programs with a polyhedral component utilizing a multiple objective linear programming solver

Demand Point Aggregation Analaysis for Location Models

Casualty Collection Points Optimization: A Study for the District of Columbia

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