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A Combinatorial Branch and Bound for the Min-Max Regret Spanning Tree Problem

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Analysis of Experimental Algorithms (SEA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11544))

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Abstract

Uncertainty in optimization can be modeled with the concept of scenarios, each of which corresponds to possible values for each parameter of the problem. The min-max regret criterion aims at obtaining a solution minimizing the maximum deviation, over all possible scenarios, from the optimal value of each scenario. Well-known problems, such as the shortest path problem and the minimum spanning tree, become NP-hard under a min-max regret criterion. This work reports the development of a branch and bound approach to solve the Minimum Spanning Tree problem under a min-max regret criterion in the discrete scenario case. The approach is tested in a wide range of test instances and compared with a generic pseudo-polynomial algorithm.

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Acknowledgments

This work was carried out in the scope of the MobiWise project: From mobile sensing to mobility advising (P2020 SAICTPAC/0011/2015), co-financed by COMPETE 2020, Portugal 2020 - POCI, European Union’s ERDF.

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Authors and Affiliations

  1. CISUC, Department of Informatics Engineering, University of Coimbra, Pólo II, 3030-290, Coimbra, Portugal

    Noé Godinho & Luís Paquete

Authors
  1. Noé Godinho
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  2. Luís Paquete
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Corresponding author

Correspondence to Noé Godinho .

Editor information

Editors and Affiliations

  1. Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias Kotsireas

  2. University of Florida, Gainesville, FL, USA

    Panos Pardalos

  3. University of Ioannina, Ioannina, Greece

    Konstantinos E. Parsopoulos

  4. Delft University of Technology, Delft, The Netherlands

    Dimitris Souravlias

  5. University of Florida, Gainesville, FL, USA

    Arsenis Tsokas

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Godinho, N., Paquete, L. (2019). A Combinatorial Branch and Bound for the Min-Max Regret Spanning Tree Problem. In: Kotsireas, I., Pardalos, P., Parsopoulos, K., Souravlias, D., Tsokas, A. (eds) Analysis of Experimental Algorithms. SEA 2019. Lecture Notes in Computer Science(), vol 11544. Springer, Cham. https://doi.org/10.1007/978-3-030-34029-2_5

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  • DOI: https://doi.org/10.1007/978-3-030-34029-2_5

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-34028-5

  • Online ISBN: 978-3-030-34029-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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