An Evolutionary Algorithm with Stochastic Hill-Climbing for the Edge-Biconnectivity Augmentation Problem

  • Ivana LjubiĆ
  • GüntherR. Raidl
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2037)


Augmenting an existing network with additional links to achieve higher robustness and survivability plays an important role in network design. We consider the problem of augmenting a network with links of minimum total cost in order to make it edge-biconnected, i.e. the failure of a single link will never disconnect any two nodes. A new evolutionary algorithm is proposed that works directly on the set of additional links of a candidate solution. Problem-specific initialization, recombination, and mutation operators use a stochastic hill-climbing procedure. With low computational effort, only locally optimal, feasible candidate solutions are produced. Experimental results are significantly better than those of a previous genetic algorithm concerning final solutions’ qualities and especially execution times.


Evolutionary Algorithm Mutation Operator Minimum Span Tree Memetic Algorithm Hybrid Genetic Algorithm 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Ivana LjubiĆ
  • GüntherR. Raidl
    • 1
  1. 1.Institute for Computer Graphics and AlgorithmsVienna University of TechnologyViennaAustria

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