Abstract
Local optima networks are a compact representation of fitness landscapes that can be used for analysis and visualisation. This paper provides the first analysis of the Asymmetric Travelling Salesman Problem using local optima networks. These are generated by sampling the search space by recording the progress of an existing evolutionary algorithm based on the Generalised Asymmetric Partition Crossover. They are compared to networks sampled through the Chained Lin-Kernighan heuristic across 25 instances. Structural differences and similarities are identified, as well as examples where crossover smooths the landscape.
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Acknowledgement
N. Veerapen and G. Ochoa are supported by the Leverhulme Trust (award number RPG-2015-395) and by the UK’s Engineering and Physical Sciences Research Council (grant number EP/J017515/1). R. Tinós is supported by FAPESP (grant 2015/06462-1) and CNPq. All data generated during this research are openly available from the Stirling Online Repository for Research Data (http://hdl.handle.net/11667/75). Results were obtained using the EPSRC funded ARCHIE-WeSt High Performance Computer (www.archie-west.ac.uk, EPSRC grant EP/K000586/1).
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Veerapen, N., Ochoa, G., Tinós, R., Whitley, D. (2016). Tunnelling Crossover Networks for the Asymmetric TSP. In: Handl, J., Hart, E., Lewis, P., López-Ibáñez, M., Ochoa, G., Paechter, B. (eds) Parallel Problem Solving from Nature – PPSN XIV. PPSN 2016. Lecture Notes in Computer Science(), vol 9921. Springer, Cham. https://doi.org/10.1007/978-3-319-45823-6_93
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