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Aggregation in hub location problems
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DOI：10.1016/j.cor.2009.01.010.png)
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Abstract
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Because of their widespread use in real-world transportation situations, hub location models have been extensively studied in the last two decades. Many types of hub location problems are NP-hard and remain unmanageable when the number of nodes exceeds 200. We present a way to tackle large-sized problems using aggregation, explore the resulting error, and show how to reduce it. Furthermore, we develop a heuristic based on aggregation for k-hub center problems and present computational results. Crown Copyright (C) 2008 Published by Elsevier Ltd. All rights reserved.
Keywords:
Hub location
Aggregation
Heuristics
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