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An improved cut-and-solve algorithm for the single-source capacitated facility location problem

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EURO Journal on Computational Optimization

Abstract

In this paper, we present an improved cut-and-solve algorithm for the single-source capacitated facility location problem. The algorithm consists of three phases. The first phase strengthens the integer program by a cutting plane algorithm to obtain a tight lower bound. The second phase uses a two-level local branching heuristic to find an upper bound, and if optimality has not yet been established, the third phase uses the cut-and-solve framework to close the optimality gap. Extensive computational results are reported, showing that the proposed algorithm runs 10–80 times faster on average compared to state-of-the-art problem-specific algorithms.

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Acknowledgements

The authors are grateful to Mr. Zhen Yang for providing the code, enabling us to compare the two algorithms, and to Professor Kim Allan Andersen for insightful comments and suggestions.

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Authors and Affiliations

  1. Department of Economics and Business Economics, School of Business and Social Sciences, Aarhus University, Fuglesangs Allé 4, 8210, Aarhus V, Denmark

    Sune Lauth Gadegaard & Lars Relund Nielsen

  2. Department of Mathematics, Science and Technology, Aarhus University, Ny Munkegade 118, 8000, Aarhus C, Denmark

    Andreas Klose

Authors
  1. Sune Lauth Gadegaard
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  2. Andreas Klose
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  3. Lars Relund Nielsen
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Correspondence to Sune Lauth Gadegaard.

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Gadegaard, S.L., Klose, A. & Nielsen, L.R. An improved cut-and-solve algorithm for the single-source capacitated facility location problem. EURO J Comput Optim 6, 1–27 (2018). https://doi.org/10.1007/s13675-017-0084-4

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  • DOI: https://doi.org/10.1007/s13675-017-0084-4

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