Dynamic Stacking Optimization in Unpredictable Environments: A Focus on Crane Scheduling
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-63223-5_13
Reference20 articles.
1. Raggl, S., Beham, A., Wagner, S., Affenzeller, M.: Effects of arrival uncertainty on solver performance in dynamic stacking problems. In: Proceedings of the 32nd European Modeling & Simulation Symposium (EMSS 2020), pp. 193–200 (2020). https://doi.org/10.46354/i3m.2020.emss.027
2. Beham, A., Leitner, S., Karder, J., Werth, B., Wagner, S.: A benchmarking framework for dynamic optimization problems in warehouse operations. In: Evolutionary Computation Conference Companion (GECCO ’22 Companion) (2022). ISBN: 978-1-4503-9268-6/22/07. https://doi.org/10.1145/3520304.3533957
3. GECCO (2023). https://gecco-2023.sigevo.org/HomePage. Accessed 05 Nov 2023
4. Raggl, S., Beham, A., Wagner, S., Affnzeller, M.: Solution approaches for the dynamic stacking problem. In: Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion, pp. 1652–1660 (2020). https://doi.org/10.1145/3377929.3398111
5. Tanaka, S., Takii, K.: A faster branch-and-bound algorithm for the block relocation problem. IEEE Trans. Autom. Sci. Eng. 13(1), 181–190 (2015). https://doi.org/10.1109/TASE.2015.2434417
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