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90 Publications


2016 | Conference Paper | LibreCat-ID: 46365
Bossek, J., & Trautmann, H. (2016). Evolving Instances for Maximizing Performance Differences of State-of-The-Art Inexact TSP Solvers. In P. Festa, M. Sellmann, & J. Vanschoren (Eds.), Learning and Intelligent Optimization (Vol. 10079, pp. 48–59). Springer International Publishing. https://doi.org/10.1007/978-3-319-50349-3_4
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2016 | Conference Paper | LibreCat-ID: 46366
Bossek, J., & Trautmann, H. (2016). Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. In G. Adorni, S. Cagnoni, M. Gori, & M. Maratea (Eds.), AI*IA 2016 Advances in Artificial Intelligence (Vol. 10037, pp. 3–12). Springer. https://doi.org/10.1007/978-3-319-49130-1_1
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2015 | Conference Paper | LibreCat-ID: 48838
Bossek, J., Bischl, B., Wagner, T., & Rudolph, G. (2015). Learning Feature-Parameter Mappings for Parameter Tuning via the Profile Expected Improvement. Proceedings of the Genetic and Evolutionary Computation Conference, 1319–1326. https://doi.org/10.1145/2739480.2754673
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2015 | Conference Paper | LibreCat-ID: 48887
Meisel, S., Grimme, C., Bossek, J., Wölck, M., Rudolph, G., & Trautmann, H. (2015). Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. Proceedings of the Genetic and Evolutionary Computation Conference , 425–432. https://doi.org/10.1145/2739480.2754705
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2015 | Conference Paper | LibreCat-ID: 46377
Meisel, S., Grimme, C., Bossek, J., Wölck, M., Rudolph, G., & Trautmann, H. (2015). Evaluation of a Multi-Objective EA on Benchmark Instances for Dynamic Routing of a Vehicle. Proceedings of the Genetic and Evolutionary Computation Conference (GECCO ’15), 425–432. https://doi.org/10.1145/2739480.2754705
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2013 | Journal Article | LibreCat-ID: 48889
Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann, F. (2013). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesperson Problem. Annals of Mathematics and Artificial Intelligence, 69(2), 151–182. https://doi.org/10.1007/s10472-013-9341-2
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2013 | Journal Article | LibreCat-ID: 46394
Mersmann, O., Bischl, B., Trautmann, H., Wagner, M., Bossek, J., & Neumann, F. (2013). A Novel Feature-Based Approach to Characterize Algorithm Performance for the Traveling Salesman Problem. Annals of Mathematics and Artificial Intelligence, 69, 151–182.
LibreCat
 

2012 | Conference Paper | LibreCat-ID: 48890
Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann, F. (2012). Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. Revised Selected Papers of the 6th International Conference on Learning and Intelligent Optimization - Volume 7219, 115–129.
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2012 | Book Chapter | LibreCat-ID: 48888
Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann, F. (2012). Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. In Learning and Intelligent Optimization (Vol. 7219, pp. 115–129). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_9
LibreCat | DOI
 

2012 | Conference Paper | LibreCat-ID: 46398
Mersmann, O., Bischl, B., Bossek, J., Trautmann, H., Wagner, M., & Neumann, F. (2012). Local Search and the Traveling Salesman Problem: A Feature-Based Characterization of Problem Hardness. In Y. Hamadi & M. Schoenauer (Eds.), Learning and Intelligent Optimization (pp. 115–129). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-34413-8_9
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