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7 Publications


2021 | Journal Article | LibreCat-ID: 45587
Habla, W., Huwe, V., & Kesternich, M. (2021). Electric and conventional vehicle usage in private and car sharing fleets in Germany. Transportation Research Part D: Transport and Environment, 93, Article 102729. https://doi.org/10.1016/j.trd.2021.102729
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2018 | Conference Paper | LibreCat-ID: 48839
Bossek, J., Grimme, C., Meisel, S., Rudolph, G., & Trautmann, H. (2018). Local Search Effects in Bi-Objective Orienteering. Proceedings of the Genetic and Evolutionary Computation Conference, 585–592. https://doi.org/10.1145/3205455.3205548
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2018 | Conference Paper | LibreCat-ID: 48885
Kerschke, P., Bossek, J., & Trautmann, H. (2018). Parameterization of State-of-the-Art Performance Indicators: A Robustness Study Based on Inexact TSP Solvers. Proceedings of the Genetic and Evolutionary Computation Conference Companion, 1737–1744. https://doi.org/10.1145/3205651.3208233
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2017 | Journal Article | LibreCat-ID: 40493
Sackel, J. (2017). Food justice, common heritage and the oceans: Resource narratives in the context of the Third United Nations Conference on the Law of the Sea. International Journal of Maritime History, 29(3), 645–659. https://doi.org/10.1177/0843871417713682
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2017 | Journal Article | LibreCat-ID: 2856
Barann, B., Beverungen, D., & Müller, O. (2017). An open-data approach for quantifying the potential of taxi ridesharing. Decision Support Systems, 99(July 2017), 86–95. https://doi.org/10.1016/j.dss.2017.05.008
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2016 | Conference Paper | LibreCat-ID: 48874
Bossek, J., & Trautmann, H. (2016). Understanding Characteristics of Evolved Instances for State-of-the-Art Inexact TSP Solvers with Maximum Performance Difference. Proceedings of the XV International Conference of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence - Volume 10037, 3–12. https://doi.org/10.1007/978-3-319-49130-1_1
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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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