Dual-based heuristics for a hierarchical covering location problem

Espejo, Luis Gonzalo Acosta; Galvão, Roberto D.; Boffey, Brian

doi:10.1016/s0305-0548(01)00087-9

Cited by 38 publications

(22 citation statements)

References 20 publications

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“…In relation to classical location problems we may cite the Lagrangean dual ascent heuristic developed by Guignard (1988) for the simple plant location problem, a comparison of Lagrangean and surrogate relaxations for the maximal covering location problem by Galvão et al (2000), the development of dual-based heuristics for a hierarchical covering location problem by Espejo et al (2003), a maximal covering location model in the presence of partial coverage by Karasakal and Karasakal (2004), and a branch-and-price approach to p-median location problems by Senne et al (2005).…”

Section: A Survey Of Subsequent Workmentioning

confidence: 99%

Hub Location Problems: The Location of Interacting Facilities

Kara

Taner

2011

International Series in Operations Research &Amp; Management Science

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), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. PrefaceThis book is the final result of a number of incidents that occurred to us while discussing location issues with colleagues at conferences. Frequently we attended presentations, in which the authors quoted the well-known references that helped to make the discipline what it is today. Upon further inquiry, though, it turned out that some of these colleagues had never actually read the original papers. We then discussed among ourselves which contributions could be credited with shaping the field. And, lo and behold, we found that we, too, had neglected to read some of the papers that form the foundation of our science. Whether it was laziness or other things that got in the way, it had become clear that something had to be done. Our first thought was to collect the original contributions (once we could agree on what they were) and reprint them. When discussing this possibility with a publisher, we immediately ran into a roadblock in the form of copyright. While this appeared to have stopped our enthusiastic effort dead in its tracks, we kept on collecting and reading what we considered original contributions.This went on until we met Camille Price, who suggested that, rather than reprinting the original contributions, we should invite some of the leaders in our field and ask them to describe the original contribution, explain and interpret it, and comment on the impact that it had to the field. This was, of course, an excellent idea, and the response by our colleagues to our pertinent requests was equally enthusiastic. What you hold in your hands is the result of this effort.In other words, the purpose of this book is to provide easy access to the main contributions to location theory. The book is organized as follows. The introductory chapter provides an overview of some of the many facets of location analysis. This is followed by contributions in the main three fields of inquiry: minisum, minimax, and covering problems. The next chapters are part of an ever-growing list of nonstandard location models: models including competitive components, those that locate undesirable facilities, those with probabilistic features, and those that allow interactions between facilities. The following chapters discuss solution techniques: after a discussion of exact and heuristic techniques, we devote an entire chapter to Weiszfeld's method, and another to Lagrangean techniques. The last chapters of this book deal with the spheres of influence that the facilities generate and that attract viii customers to them, an...

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Section: A Survey Of Subsequent Workmentioning

confidence: 99%

Hub Location Problems: The Location of Interacting Facilities

Kara

Taner

2011

International Series in Operations Research &Amp; Management Science

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“…This particular problem looked at locating facilities that provided different levels of service to the demand nodes. Espejo et al [9] expanded on the HCLP model, developing solutions using dual-based heuristics; specifically, a subgradientbased heuristic incorporating a Lagrangean-surrogate relaxation, which reduced to a 0-1 knapsack problem. Megiddo et al [10] considered locating new facilities within a pre-existing network of established facilities, with the goal of "drawing" a maximum number of customers.…”

Section: Location Modelingmentioning

confidence: 99%

A location analysis approach for military maintenance scheduling with geographically dispersed service areas

Overholts

Bell

Arostegui

2009

Omega

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“…Com a finalidade de ilustrar, para o HCLP, o desempenho da relaxação combinada L-S em relação às relaxações Lagrangeana e surrogate, reproduzimos na tabela abaixo os resultados obtidos em Espejo et al (2003). Os problemas-teste utilizados nessa tabela foram os seguintes: S55, rede definida por Swain (1971); G&R100 e G&R150, que correspondem às redes geradas aleatoriamente por Galvão & ReVelle (1996); B300, B500 e B700, obtidos da biblioteca eletrônica de Beasley para o problema das p-medianas (problemas Pmed11, Pmed21 e Pmed31).…”

Section: Ilustração Do Uso De Umaunclassified

“…Nossa experiência prática em resolver o problema da mochila com coeficientes fracionários explica o porque destes resultados. Maiores detalhes podem ser encontrados em Espejo et al (2003).…”

Section: Ilustração Do Uso De Umaunclassified

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Espejo¹,

Galvão²

2002

Pesqui. Oper.

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ResumoAs diferentes relaxações de um problema de programação inteira permitem que se obtenham limites da solução ótima do mesmo. Entre as relaxações mais usadas destacam-se as de programação linear, Lagrangeana, surrogate e combinada Lagrangeana-surrogate (L-S). O presente trabalho contém uma revisão bibliográfica destas relaxações, de métodos de solução para os duais respectivos e de relações teóricas existentes entre os duais. É dada ênfase especial à relaxação surrogate e a relaxações combinadas Lagrangeana-surrogate. Ilustra-se o uso de uma relaxação combinada L-S através da aplicação da mesma a um problema de localização hierárquico com restrições de cobertura.Palavras-chave: relaxações: Lagrangeana, surrogate e combinada Lagrangeana-surrogate; limites para a programação inteira. AbstractRelaxations of an integer programming problem produce bounds on its optimal solution. The linear programming, Lagrangean, surrogate and combined Lagrangean-surrogate (L-S) relaxations are the most commonly used in the solution of an integer programming problem. We present a brief review of these relaxations, solution methods for the respective duals and theoretical relationships that exist among them. We give special emphasis to surrogate and combined L-S relaxations. The use of a combined L-S relaxation is illustrated through its application to a hierarchical covering location problem.

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Dual-based heuristics for a hierarchical covering location problem

Cited by 38 publications

References 20 publications

Hub Location Problems: The Location of Interacting Facilities

Hub Location Problems: The Location of Interacting Facilities

A location analysis approach for military maintenance scheduling with geographically dispersed service areas

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