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Conference Paper (published)

The Effect of Landscape Funnels in QAPLIB Instances

Details

Citation

Thomson S, Ochoa G, Daolio F & Veerapen N (2017) The Effect of Landscape Funnels in QAPLIB Instances. In: Proceedings of the Genetic and Evolutionary Computation Conference Companion 2017, Berlin, Germany, July 15–19, 2017 (GECCO ’17). GECCO ’17: The Genetic and Evolutionary Computation Conference, Berlin, Germany, 15.07.2017-19.07.2017. New York: ACM, pp. 1495-1500. https://doi.org/10.1145/3067695.3082512

Abstract
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 are 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.

Keywords
Fitness Landscapes; Quadratic Assignment Problem; Local Optima Networks; Funnel Landscapes; Combinatorial Optimisation

StatusPublished
Publication date31/12/2017
Publication date online31/07/2017
URL
PublisherACM
Place of publicationNew York
ISBN978-1-4503-4939-0
ConferenceGECCO ’17: The Genetic and Evolutionary Computation Conference
Conference locationBerlin, Germany
Dates

People (1)

Professor Gabriela Ochoa

Professor Gabriela Ochoa

Professor, Computing Science

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Research centres/groups