Abstract
We consider the Capacitated Single Allocation Hub Location Problem (CSAHLP) in which the objective is to choose the set of hubs from all nodes in a given network in such way that the allocation of all the nodes to the chosen hubs is optimal. We propose a Relaxation Adaptive Memory Programming (RAMP) approach for the CSAHLP. Our method combines Lagrangean Subgradient search with an improvement method to explore primal-dual relationships and create advanced memory structures that integrate information from both primal and dual solutions spaces. The algorithm was tested on the standard dataset and produced extremely competitive results that include new best-known solutions. Comparisons with the current best performing algorithms for the CSAHLP show that our RAMP algorithm exhibits excellent results.
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Matos, T., Gamboa, D. (2017). Dual-RAMP for the Capacitated Single Allocation Hub Location Problem. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2017. ICCSA 2017. Lecture Notes in Computer Science(), vol 10405. Springer, Cham. https://doi.org/10.1007/978-3-319-62395-5_48
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DOI: https://doi.org/10.1007/978-3-319-62395-5_48
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