Research Output
The effect of landscape funnels in QAPLIB instances
  The effectiveness of common metaheuristics on combinatorial optimisation problems can be limited by certain characteristics of the fitness landscape. We use the local optima network model to compress the 'inherent structure' of a problem space into a network whose structure relates to the empirical hardness of the underlying landscape. Monotonic sequences axe used on the local optima networks of a benchmark set of QAP instances (QAPLIB) to expose landscape funnels. The results suggest links between features of these structures and lowered metaheuristic performance.

  • Date:

    15 July 2017

  • Publication Status:

    Published

  • Publisher

    ACM

  • DOI:

    10.1145/3067695.3082512

  • Funders:

    Engineering and Physical Sciences Research Council; Leverhulme Trust

Citation

Thomson, S. L., Ochoa, G., Daolio, F., & Veerapen, N. (2017, July). The effect of landscape funnels in QAPLIB instances. Presented at GECCO '17: Genetic and Evolutionary Computation Conference, Berlin, Germany

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