|Appears in Collections:||Computing Science and Mathematics Conference Papers and Proceedings|
|Peer Review Status:||Refereed|
|Title:||The Effect of Landscape Funnels in QAPLIB Instances|
|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), New York: ACM. GECCO ’17: The Genetic and Evolutionary Computation Conference, 15.7.2017 - 19.7.2017, Berlin, Germany, pp. 1495-1500.|
|Conference Name:||GECCO ’17: The Genetic and Evolutionary Computation Conference|
|Conference Location:||Berlin, Germany|
|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.|
|Status:||Book Chapter: author post-print (pre-copy editing)|
|Rights:||© 2017 Copyright held by the owner/author(s) GECCO ’17, Berlin, Germany Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profi t or commercial advantage and that copies bear this notice and the full citation on the fi rst page. Copyrights for third-party components of this work must be honored. For all other uses, contact the owner/author(s).|
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