Single-assignment hub location problems with multiple capacity levels

Correia, Isabel; Nickel, Stefan; Saldanha-da-Gama, Francisco

doi:10.1016/j.trb.2009.12.016

Cited by 88 publications

(46 citation statements)

References 22 publications

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“…This formulation was cited in [17] as being the best computationally effective. It has been proved as efficient for many variants of the Hub Location problem [18], [19], the transportation problem [20] and many other problems.…”

Section: Problem Descriptionmentioning

confidence: 99%

Traffic-aware virtual machine placement in geographically distributed Clouds

Teyeb

Balma

Hadj-Alouane

et al. 2014

2014 International Conference on Control, Decision and Information Technologies (CoDIT)

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In this work, we focus on the problem of virtual machines (VMs) placement in geographically distributed data centers, where tenants may require a set of networking VMs. The aim of the present work is to plan and optimize the placement of tenant's VMs in a distributed Cloud environment while considering location and system performance constraints. Thus, we propose ILP formulations which have as objective the minimization of traffic generated by networking VMs and circulating on the backbone network. The different experiments conducted on the proposed formulations show the effectiveness of our model for large-scale Cloud systems in terms of running time and computational resources.

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Section: Problem Descriptionmentioning

confidence: 99%

Traffic-aware virtual machine placement in geographically distributed Clouds

Teyeb

Balma

Hadj-Alouane

et al. 2014

2014 International Conference on Control, Decision and Information Technologies (CoDIT)

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“…The relevant international literature provides a great number of scientific contributions that deal with transportation and logistics hubs within hub-and-spoke systems and intermodal logistics networks, as well as their design and allocation problems, with particular emphasis on dry ports (see e.g. Jarzemskis and Vasiliauskas 2007, Correia et al 2010a, 2010b, Ishfaq and Sox 2011. Moreover, scientific research has also focused on the significance of logistics hubs as well as on the design of logistical networks (see e.g.…”

Section: Literature Reviewmentioning

confidence: 99%

Management of freight villages: findings from an exploratory study in Germany

Winkler

Seebacher

2011

International Journal of Logistics Research and Applications

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This paper aims to outline appropriate measures for generating positive effects resulting from the synergy-oriented management of freight villages (FVs). An exploratory study was conducted to investigate the development and management of FVs in Germany. This paper provides an overview of the most important empirical results regarding the development and synergy-oriented operation of FVs. Furthermore, it identifies the need for comprehensive and well-coordinated management to increase synergy for the companies involved. In conclusion, the most crucial implications for FV management are highlighted. Our recommendations for action, if implemented, could lead to greater efficiency and lower costs due to improved logistical performance.

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“…Reference [41] proposed approximation algorithms for solving the single allocation problem. Reference [42] studied single allocation problems with multiple capacity levels, where the decision making process includes the size of hubs. An enhanced Benders decomposition (EBD) algorithm was used to solve multiple allocation uncapacitated hub location problem for large-scale networks by [29].…”

Section: Introductionmentioning

confidence: 99%

Finding p-Hub Median Locations: An Empirical Study on Problems and Solution Techniques

Sun

Dai

Zhang

et al. 2017

Journal of Advanced Transportation

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Hub location problems have been studied by many researchers for almost 30 years, and, accordingly, various solution methods have been proposed. In this paper, we implement and evaluate several widely used methods for solving five standard hub location problems. To assess the scalability and solution qualities of these methods, three well-known datasets are used as case studies: Turkish Postal System, Australia Post, and Civil Aeronautics Board. Classical problems in small networks can be solved efficiently using CPLEX because of their low complexity. Genetic algorithms perform well for solving three types of single allocation problems, since the problem formulations can be neatly encoded with chromosomes of reasonable size. Lagrangian relaxation is the only technique that solves reliable multiple allocation problems in large networks. We believe that our work helps other researchers to get an overview on the best solution techniques for the problems investigated in our study and also stipulates further interest on cross-comparing solution techniques for more expressive problem formulations.

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Single-assignment hub location problems with multiple capacity levels

Cited by 88 publications

References 22 publications

Traffic-aware virtual machine placement in geographically distributed Clouds

Traffic-aware virtual machine placement in geographically distributed Clouds

Management of freight villages: findings from an exploratory study in Germany

Finding p-Hub Median Locations: An Empirical Study on Problems and Solution Techniques

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