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Soft Computing
Published in: Soft Computing 8/2015

01-08-2015 | Methodologies and Application

Developing equilibrium optimization methods for hub location problems

Authors: Kai Yang, Yankui Liu

Published in: Soft Computing | Issue 8/2015

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Abstract

This paper develops three new equilibrium optimization models for \(p\)-hub center problem, in which the travel times are characterized by fuzzy random variables. The proposed equilibrium optimization methods are to find the locations of hub facilities and demand nodes so as to maximize equilibrium service levels of uncertain travel times. Under mild assumptions, we first handle equilibrium service levels and reduce them to their equivalent probability constraints. According to structural characteristics of equivalent stochastic programming models, we design a new parametric decomposition-based hybrid tabu search (PD-HTS) algorithm that incorporates parametric decomposition (PD), sample average approximation and tabu search algorithm. To demonstrate the effectiveness of designed solution method, we conduct some numerical experiments by using Australian Post data set and randomly generated data set. The comparison study shows that the PD-HTS algorithm exhibits better performance than the parametric decomposition-based hybrid genetic algorithm.
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Metadata
Title
Developing equilibrium optimization methods for hub location problems
Authors
Kai Yang
Yankui Liu
Publication date
01-08-2015
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 8/2015
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-014-1427-1

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