1996
DOI: 10.1016/0377-2217(95)00100-x
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Tight linear programming relaxations of uncapacitated p-hub median problems

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Cited by 367 publications
(228 citation statements)
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“…The -hub median problem aims to select hub facilities from a set of available candidates, to allocate spoke nodes to hubs and to simultaneously route freight flows. There are two kinds of mathematical models to formulate the hub-and-spoke network problem, including path-based mixed integer linear programming models with four-dimensional variables (e.g., [9][10][11][12]) and origin-based mixed integer linear programming models with three-dimensional variables (e.g., [13][14][15]). Meng and Wang [3], both, apply a mathematical program with equilibrium constraints model for the intermodal hub-and-spoke network design problem with multiple stakeholders and multitype containers.…”
Section: Literature Reviewmentioning
confidence: 99%
“…The -hub median problem aims to select hub facilities from a set of available candidates, to allocate spoke nodes to hubs and to simultaneously route freight flows. There are two kinds of mathematical models to formulate the hub-and-spoke network problem, including path-based mixed integer linear programming models with four-dimensional variables (e.g., [9][10][11][12]) and origin-based mixed integer linear programming models with three-dimensional variables (e.g., [13][14][15]). Meng and Wang [3], both, apply a mathematical program with equilibrium constraints model for the intermodal hub-and-spoke network design problem with multiple stakeholders and multitype containers.…”
Section: Literature Reviewmentioning
confidence: 99%
“…[37] propose mixed integer formulations for both SA and MA p-hub HLPs that yield tight linear relaxations.…”
Section: Literature Reviewmentioning
confidence: 99%
“…A similar strategy is also applied to SA p-hub HLP. Pirkul and Schilling [35] propose a Lagrangian relaxation approach to the SA p-hub model presented in Skorin-Kapov et al [37]. By adding a new type of cut constraints, their algorithm is very effective in generating optimal solutions.…”
Section: Literature Reviewmentioning
confidence: 99%
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