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Please use this identifier to cite or link to this item: http://hdl.handle.net/11667/75
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dc.contributorVeerapen, Nadarajen-
dc.contributor.otherEPSRC - Engineering and Physical Sciences Research Councilen_GB
dc.contributor.otherLeverhulme Trusten_GB
dc.creatorVeerapen, Nadarajen-
dc.creatorOchoa, Gabriela-
dc.creatorTinos, Renato-
dc.creatorWhitley, L Darrell-
dc.date.accessioned2016-06-13T12:11:39Z-
dc.date.available2016-06-13T12:11:39Z-
dc.date.created2016-
dc.identifier.urihttp://hdl.handle.net/11667/75-
dc.description.abstractThe dataset contains landscape data for "Tunnelling Crossover Networks for the Asymmetric TSP", N. Veerapen, G. Ochoa, R. Tinós, D. Whitley, The 14th International Conference on Parallel Problem Solving from Nature, PPSN2016, 17-21 September 2016, Edinburgh, Scotland. The dataset describes the network structure of the local optima networks for the 25 Asymmetric Traveling Salesman Problem instances that are sampled in the paper according to two different methodologies: using an evolutionary algorithm based on the Generalized Partition Crossover, and using Chained Lin-Kernighan.en_GB
dc.description.tableofcontentsThe dataset contains landscape data for "Tunnelling Crossover Networks for the Asymmetric TSP", N. Veerapen, G. Ochoa, R. Tinós, D. Whitley, The 14th International Conference on Parallel Problem Solving from Nature, PPSN2016, 17-21 September 2016, Edinburgh, Scotland. The dataset describes the network structure of the local optima networks for the 25 Asymmetric Traveling Salesman Problem instances that are sampled in the paper according to two different methodologies: using an evolutionary algorithm based on the Generalized Partition Crossover, and using Chained Lin-Kernighan. The data are organised into three zip files, one for each method and one for generated instances. These instances (C50.0, C100.0, C200.0, E50.0, E100.0, and E200.0) were generated using the DIMACS TSP instance generator (http://dimacs.rutgers.edu/Challenges/TSP/download.html) and the distance matrices were perturbed to obtained asymmetric instances. The rest of the instances are from TSPLIB (http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/). Additional details are provided in the readme.txt file.en_GB
dc.publisherUniversity of Stirling. Faculty of Natural Sciences.en_GB
dc.relationVeerapen, N; Ochoa, G; Tinos, R; Whitley, LD (2016): Data from ''Tunnelling Crossover Networks for the Asymmetric TSP". University of Stirling. Faculty of Natural Sciences. Dataset. http://hdl.handle.net/11667/75en_GB
dc.relation.isreferencedbyVeerapen N., Ochoa G., Tinós R. and Whitley, D. (2016) Tunnelling Crossover Networks for the Asymmetric TSP In: Handl J, Hart E, Lewis PR, Lopez-Ibanez M, Ochoa G, Paechter B (ed.) Parallel Problem Solving from Nature – PPSN XIV: 14th International Conference, Edinburgh, UK, September 17-21, 2016, Proceedings, Cham, Switzerland: Springer. PPSN2016 - 14th International Conference on Parallel Problem Solving from Nature, 17.9.2016 - 21.9.2016, Edinburgh, pp. 994-1003. DOI: https://doi.org/10.1007/978-3-319-45823-6_93 Available at: http://hdl.handle.net/1893/24061en_GB
dc.rightsRights covered by the standard CC-BY 4.0 licence: https://creativecommons.org/licenses/by/4.0/en_GB
dc.subjectLocal Optima Networken_GB
dc.subjectAsymmetric Traveling Salesman Problemen_GB
dc.subjectFitness Landscapeen_GB
dc.subjectLocal Searchen_GB
dc.subjectGenetic Algorithmen_GB
dc.subject.classification::Information and communication technologies::Artificial Intelligence Technologies::Computational Searchen_GB
dc.subject.classification::Information and communication technologies::Artificial Intelligence Technologies::Meta Heuristicsen_GB
dc.subject.classification::Information and communication technologies::Artificial Intelligence Technologies::Optimisation (AI)en_GB
dc.titleData from ''Tunnelling Crossover Networks for the Asymmetric TSP"en_GB
dc.typedataseten_GB
dc.contributor.emailnve@cs.stir.ac.uken_GB
dc.identifier.projectidRPG-2015-395en_GB
dc.identifier.projectidEP/J017515/1en_GB
dc.title.projectThe Cartography of Computational search spacesen_GB
dc.title.projectDAASE: Dynamic Adaptive Automated Software Engineeringen_GB
dc.contributor.affiliationUniversity of Stirling (Computing Science - CSM Dept)en_GB
dc.contributor.affiliationUniversity of Sao Pauloen_GB
dc.contributor.affiliationColorado State Universityen_GB
dc.date.publicationyear2016en_GB
dc.identifier.wtid415580-
dc.identifier.wtid418227-
Appears in Collections:University of Stirling Research Data

Files in This Item:
File Description SizeFormat 
gapx.zipNetworks generated with the GAPX-based GA1.44 GBUnknownView/Open
gen_instances.zipGenerated Instances681.85 kBUnknownView/Open
clk.zipNetworks generated with Chained Lin-Kernighan366.57 MBUnknownView/Open
readme.txtDescription of file organisation, names and structure5.93 kBTextView/Open


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