A hybrid Outer-Approximation/Benders Decomposition algorithm for the single allocation hub location problem under congestion

An efficient procedure that concurrently generates Outer-Approximation and Benders cuts is devised to tackle the single allocation hub location problem under congestion, an MINLP. The proposed method is able to optimally solve large instances (up to 200 nodes) in reasonable time. The combination of...

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Vydáno v:Operations research letters Ročník 39; číslo 5; s. 329 - 337
Hlavní autoři: de Camargo, Ricardo Saraiva, de Miranda, Gilberto, Ferreira, Ricardo P.M.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Oxford Elsevier B.V 01.09.2011
Elsevier
Témata:
Algorithms
Allocations
Applied sciences
Benders Decomposition
Bending machines
Congestion
Exact sciences and technology
Hub-and-spoke networks
Logistics
Mathematical programming
Mixed integer nonlinear programming
Operational research and scientific management
Operational research. Management science
Operations research
Optimization
Outer-approximation algorithms
Position (location)
Hub-and-spoke networks
Mixed integer nonlinear programming
Outer-approximation algorithms
Benders Decomposition
Partition method
Network hub
Resource allocation
Algorithmics
Linear programming
Mixed integer programming
Non linear programming
Approximation algorithm
Location problem
Traffic congestion
Logistics
Novelty
ISSN:0167-6377, 1872-7468
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Shrnutí:An efficient procedure that concurrently generates Outer-Approximation and Benders cuts is devised to tackle the single allocation hub location problem under congestion, an MINLP. The proposed method is able to optimally solve large instances (up to 200 nodes) in reasonable time. The combination of both cuts is an algorithmic novelty. ► Hub-and-spoke systems with single assignment are specially vulnerable to congestion. ► A new scheme concurrently using Outer-Approximation and Benders method is devised. ► The proposed approach is used to compare two well-known congestion cost functions. ► Even when fitted to each other, the congestion functions yield different networks. ► Large instances, never reported before, are solved to optimality.
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ISSN:0167-6377
1872-7468
DOI:10.1016/j.orl.2011.06.015