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A Hybrid Primal Heuristic for Robust Multiperiod Network Design

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Applications of Evolutionary Computation (EvoApplications 2014)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8602))

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Abstract

We investigate the Robust Multiperiod Network Design Problem, a generalization of the classical Capacitated Network Design Problem that additionally considers multiple design periods and provides solutions protected against traffic uncertainty. Given the intrinsic difficulty of the problem, which proves challenging even for state-of-the art commercial solvers, we propose a hybrid primal heuristic based on the combination of ant colony optimization and an exact large neighborhood search. Computational experiments on a set of realistic instances from the SNDlib show that our heuristic can find solutions of extremely good quality with low optimality gap.

This work was partially supported by the German Research Foundation (DFG), project Multiperiod Network Optimization, by the DFG Research Center Matheon (www.matheon.de), Project B3, and by the German Federal Ministry of Education and Research (BMBF), project ROBUKOM [1], grant 05M10PAA.

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Author information

Authors and Affiliations

  1. DFG Research Center MATHEON, Technical University Berlin, Straße des 17. Juni 135, 10623, Berlin, Germany

    Fabio D’Andreagiovanni

  2. Department of Optimization, Zuse-Institute Berlin (ZIB), Takustr. 7, 14195, Berlin, Germany

    Fabio D’Andreagiovanni, Jonatan Krolikowski & Jonad Pulaj

Authors
  1. Fabio D’Andreagiovanni
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  2. Jonatan Krolikowski
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  3. Jonad Pulaj
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Corresponding author

Correspondence to Fabio D’Andreagiovanni .

Editor information

Editors and Affiliations

  1. Depto. Estadística e Investigación, Universidad Politécnica de Valencia, Valencia, Spain

    Anna I. Esparcia-Alcázar

  2. University of Granada, Granada, Spain

    Antonio M. Mora

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D’Andreagiovanni, F., Krolikowski, J., Pulaj, J. (2014). A Hybrid Primal Heuristic for Robust Multiperiod Network Design. In: Esparcia-Alcázar, A., Mora, A. (eds) Applications of Evolutionary Computation. EvoApplications 2014. Lecture Notes in Computer Science(), vol 8602. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-45523-4_2

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  • DOI: https://doi.org/10.1007/978-3-662-45523-4_2

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  • Print ISBN: 978-3-662-45522-7

  • Online ISBN: 978-3-662-45523-4

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