In this repository you find the simulation environments and policies to get started into benchmarking dynamic stacking problems. For more information on how to get started with running tests and benchmarks on your own machine, please refer to the documentation given at simulation/README.md.

If you intend to do research using DynStack we refer to the following papers. We're happy to also include your paper, please contact us at dynstack@adaptop.at.

• Beham, A., Leitner, S., Karder, J., Werth, B., Wagner, S. 2022. DynStack - A Benchmarking Framework for Dynamic Optimization Problems in Warehouse Operations. In Proceedings of the 2022 Genetic and Evolutionary Computation Conference Companion (GECCO '22). Association for Computing Machinery, pp. 1984-1991. https://dl.acm.org/doi/10.1145/3520304.3533957
• Karder, J. A., Beham, A., Werth, B., Wagner, S., Affenzeller, M. 2022. Integrated Machine Learning in Open-Ended Crane Scheduling: Learning Movement Speeds and Service Times. In Procedia Computer Science (Vol. 200, pp. 1031) https://www.sciencedirect.com/science/article/pii/S1877050922003118
• Beham, A., Raggl, S., Karder, J., Werth, B., Wagner, S. 2022. Dynamic Warehouse Environments for Crane Stacking and Scheduling. Procedia Computer Science, 200, 1461-1470. https://doi.org/10.1016/j.procs.2022.01.347
• Werth, B.; Karder, J.; Beham, A.; Wagner, S. 2021. Dynamic landscape analysis for open-ended stacking. In Proceedings of the 2021 Genetic and Evolutionary Computation Conference Companion (GECCO '21). Association for Computing Machinery, pp. 1700-1707. https://dl.acm.org/doi/10.1145/3449726.3463153
• Raggl, S.; Beham, A.; Wagner, S; Affenzeller, M. 2020. Effects of Arrival Uncertainty on Solver Performance in Dynamic Stacking Problems. Proceedings of the 32nd European Modeling and Simulation Symposium EMSS2020, pp. 193-200. https://doi.org/10.46354/i3m.2020.emss.027
• Raggl, S.; Beham, A.; Wagner, S; Affenzeller, M. 2020. Solution Approaches for the Dynamic Stacking Problem. In Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion (GECCO '20). Association for Computing Machinery, pp. 1652-1660. https://dl.acm.org/doi/10.1145/3377929.3398111