Benders Decomposition for the Hop-Constrained Survivable Network Design Problem

  • Authors:
  • Quentin Botton;Bernard Fortz;Luis Gouveia;Michael Poss

  • Affiliations:
  • Center for Supply Chain Management, Louvain School of Management, and Center for Operations Research and Econometrics, Université Catholique de Louvain, B-1348 Louvain-la-Neuve, Belgium;Graphes et Optimisation Mathématique, Department of Computer Science, Faculté des Sciences, Université Libre de Bruxelles, B-1050 Brussels, Belgium;Departamento de Estatística e Investigação Operacional--Centro de Investigação Operacional, Faculdade de Ciências da Universidade de Lisboa, 1749-016 Lisbon, Portugal;Graphes et Optimisation Mathématique, Department of Computer Science, Faculté des Sciences, Université Libre de Bruxelles, B-1050 Brussels, Belgium

  • Venue:
  • INFORMS Journal on Computing
  • Year:
  • 2013

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Abstract

Given a graph with nonnegative edge weights and node pairs Q, we study the problem of constructing a minimum weight set of edges so that the induced subgraph contains at least K edge-disjoint paths containing at most L edges between each pair in Q. Using the layered representation introduced by Gouveia [Gouveia, L. 1998. Using variable redefinition for computing lower bounds for minimum spanning and Steiner trees with hop constraints. INFORMS J. Comput.102 180--188], we present a formulation for the problem valid for any K, L ≥ 1. We use a Benders decomposition method to efficiently handle the large number of variables and constraints. We show that our Benders cuts contain constraints used in previous studies to formulate the problem for L = 2, 3, 4, as well as new inequalities when L ≥ 5. Whereas some recent works on Benders decomposition study the impact of the normalization constraint in the dual subproblem, we focus here on when to generate the Benders cuts. We present a thorough computational study of various branch-and-cut algorithms on a large set of instances including the real-based instances from SNDlib. Our best branch-and-cut algorithm combined with an efficient heuristic is able to solve the instances significantly faster than CPLEX 12 on the extended formulation.