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Journal of Advanced Transportation
Volume 2017, Article ID 9387302, 23 pages
Review Article

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

1School of Electronic and Information Engineering, Beihang University, Beijing 100191, China
2Beijing Key Laboratory for Network-Based Cooperative ATM, Beijing 100191, China
3Department of Civil and Environmental Engineering, University of South Florida, Tampa, FL 33620, USA
4College of Air Traffic Management, Civil Aviation University of China, Tianjin 300300, China
5College of Transportation Engineering, Tongji University, Shanghai 200092, China

Correspondence should be addressed to Sebastian Wandelt; ed.nilreb-uh.kitamrofni@tlednaw

Received 18 May 2017; Revised 22 October 2017; Accepted 31 October 2017; Published 23 November 2017

Academic Editor: Zhi-Chun Li

Copyright © 2017 Xiaoqian Sun et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.