Titlebook: Computational Logistics; 14th International C Joachim R. Daduna,Gernot Liedtke,Stefan Voß Conference proceedings 2023 The Editor(s) (if app

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书目名称Computational Logistics影响因子(影响力)




书目名称Computational Logistics影响因子(影响力)学科排名




书目名称Computational Logistics网络公开度




书目名称Computational Logistics网络公开度学科排名




书目名称Computational Logistics被引频次




书目名称Computational Logistics被引频次学科排名




书目名称Computational Logistics年度引用




书目名称Computational Logistics年度引用学科排名




书目名称Computational Logistics读者反馈




书目名称Computational Logistics读者反馈学科排名

engrave

ACE-inhibitor

https://doi.org/10.1007/978-3-031-43612-3computational logistics; maritime shipping; container terminal; vehicle routing; combinatorial optimizat

CYT

Immunoglobulin

形上升才刺激

https://doi.org/10.1007/978-3-658-33729-2drivers). Thus, the efficiency of such operating model lies in the successful matching of demand and supply, i.e., how to match the delivery tasks with suitable drivers that will result in successful assignment and completion of the tasks. We consider a Same-Day Delivery Problem (SDDP) involving a P

形上升才刺激

Vorbereitung der empirischen Erhebungollecting and delivering these items within a hospital can be modeled as a Pickup and Delivery Problem with Time Windows (PDPTW). This paper proposes a hybrid dynamic optimization to address the IHL problem based on a two-step heuristic. This algorithm combines reactive and periodic optimizations to

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Isometric

愚笨

Angelika Schmidt-Koddenberg,Annette Mülleryage. Due to a large variety of combinatorial aspects, a scalable algorithm to solve a representative problem is yet to be found. This paper will show that deep reinforcement learning can optimize a non-trivial master bay planning problem. Our experiments show that proximal policy optimization effic