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http://hdl.handle.net/11667/75| Appears in Collections: | University of Stirling Research Data |
| Title: | Data from ''Tunnelling Crossover Networks for the Asymmetric TSP" |
| Creator(s): | Veerapen, Nadarajen Ochoa, Gabriela Tinos, Renato Whitley, L Darrell |
| Contact Email: | nve@cs.stir.ac.uk |
| Keywords: | Local Optima Network Asymmetric Traveling Salesman Problem Fitness Landscape Local Search Genetic Algorithm |
| Date Available: | 13-Jun-2016 |
| Citation: | Veerapen, 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/11667/75 |
| Publisher: | University of Stirling. Faculty of Natural Sciences. |
| Dataset Description (Abstract): | The 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. |
| Dataset Description (TOC): | The 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. |
| Type: | dataset |
| Contract/Grant Title: | The Cartography of Computational search spaces DAASE: Dynamic Adaptive Automated Software Engineering |
| Funder(s): | EPSRC - Engineering and Physical Sciences Research Council Leverhulme Trust |
| Contract/Grant Number: | RPG-2015-395 EP/J017515/1 |
| Worktribe Project ID: | 415580 418227 |
| URI: | http://hdl.handle.net/11667/75 |
| Rights: | Rights covered by the standard CC-BY 4.0 licence: https://creativecommons.org/licenses/by/4.0/ |
| Affiliation(s) of Dataset Creator(s): | University of Stirling (Computing Science - CSM Dept) University of Sao Paulo Colorado State University |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| gapx.zip | Networks generated with the GAPX-based GA | 1.44 GB | Unknown | View/Open |
| gen_instances.zip | Generated Instances | 681.85 kB | Unknown | View/Open |
| clk.zip | Networks generated with Chained Lin-Kernighan | 366.57 MB | Unknown | View/Open |
| readme.txt | Description of file organisation, names and structure | 5.93 kB | Text | View/Open |
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