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Ivan Contreras

Bio: Ivan Contreras is an academic researcher from Concordia University Wisconsin. The author has contributed to research in topics: Network planning and design & Integer programming. The author has an hindex of 23, co-authored 46 publications receiving 1779 citations. Previous affiliations of Ivan Contreras include Universidad de las Américas Puebla & Polytechnic University of Catalonia.

Papers
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Journal ArticleDOI
TL;DR: A Monte-Carlo simulation-based algorithm is described that integrates a sample average approximation scheme with a Benders decomposition algorithm to solve problems having stochastic independent transportation costs.

201 citations

Journal ArticleDOI
TL;DR: This paper describes an exact algorithm capable of solving large-scale instances of the well-known uncapacitated hub location problem with multiple assignments by applying Benders decomposition to a strong path-based formulation of the problem.
Abstract: This paper describes an exact algorithm capable of solving large-scale instances of the well-known uncapacitated hub location problem with multiple assignments. The algorithm applies Benders decomposition to a strong path-based formulation of the problem. The standard decomposition algorithm is enhanced through the inclusion of several features such as the use of a multicut reformulation, the generation of strong optimality cuts, the integration of reduction tests, and the execution of a heuristic procedure. Extensive computational experiments were performed to evaluate the efficiency and robustness of the algorithm. Computational results obtained on classical benchmark instances (with up to 200 nodes) and on a new and more difficult set of instances (with up to 500 nodes) confirm the efficiency of the algorithm.

196 citations

Book ChapterDOI
01 Jan 2015
TL;DR: This chapter overviews the key distinguishing features, assumptions and properties commonly considered in HLPs, and highlights the role location and network design decisions play in the formulation and solution of HLPs.
Abstract: Hub Location Problems (HLPs) lie at the heart of network design planning in transportation and telecommunication systems. They are a challenging class of optimization problems that focus on the location of hub facilities and on the design of hub networks. This chapter overviews the key distinguishing features, assumptions and properties commonly considered in HLPs. We highlight the role location and network design decisions play in the formulation and solution of HLPs. We also provide a concise overview of the main developments and most recent trends in hub location research. We cover various topics such as hub network topologies, flow dependent discounted costs, capacitated models, uncertainty, dynamic and multi-modal models, and competition and collaboration. We also include a summary of the most successful integer programming formulations and efficient algorithms that have been recently developed for the solution of HLPs.

164 citations

Journal ArticleDOI
TL;DR: This paper presents the Tree of Hubs Location Problem, a network hub location problem with single assignment where a fixed number of hubs have to be located, with the particularity that it is required that the hubs are connected by means of a tree.

150 citations

Journal ArticleDOI
TL;DR: A unified framework for the general network design problem which encompasses several classical problems involving combined location and network design decisions, and relevant modeling aspects, alternative formulations and possible algorithmic strategies are presented and analyzed.

122 citations


Cited by
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Journal Article
TL;DR: In this paper, integer programming formulations for four types of discrete hub location problems are presented: the p-hub median problem, the uncapacitated hub location problem, p -hub center problems and hub covering problems.

727 citations

Journal ArticleDOI
TL;DR: A state-of-the-art survey of the Benders Decomposition algorithm, emphasizing its use in combinatorial optimization and introducing a taxonomy of algorithmic enhancements and acceleration strategies based on the main components of the algorithm.

506 citations

Journal ArticleDOI
TL;DR: This paper focuses on reviewing the most recent advances in HLP from 2007 up to now, and a review of all variants of HLPs (i.e., network, continuous, and discrete HLPs) is provided.

471 citations

Journal ArticleDOI
TL;DR: Insight into early motivations for analyzing hub location problems are provided and linkages to problems in location analysis and network design are described to suggest promising directions for future effort.
Abstract: Last year was the 25th anniversary of two seminal transportation hub location publications, which appeared in 1986 in Transportation Science and Geographical Analysis. Though there are related hub location and network design articles that predate these works, the 1986 publications provided a key impetus for the growth of hub location as a distinct research area. This paper is not intended as a comprehensive review of hub location literature; rather, our goal is to reflect on the origins of hub location research, especially in transportation, and provide some commentary on the present status of the field. We provide insight into early motivations for analyzing hub location problems and describe linkages to problems in location analysis and network design. We also highlight some of the most recent research, discuss some shortcomings of hub location research and suggest promising directions for future effort.

454 citations

01 May 1996
TL;DR: In this article, the authors consider a bilevel model where the leader wants to maximize revenues from a taxation scheme, while the follower rationally reacts to those tax levels, and focus their attention on the special case of a toll-setting problem defined on a multicommodity transportation network.
Abstract: We consider a bilevel model where the leader wants to maximize revenues from a taxation scheme, while the follower rationally reacts to those tax levels. We focus our attention on the special case of a toll-setting problem defined on a multicommodity transportation network. We show that the general problem is NP-complete, while particular instances are polynomially solvable. Numerical examples are given.

319 citations