Titlebook: Computational Logistics; 15th International C Alexander Garrido,Carlos D. Paternina-Arboleda,Ste Conference proceedings 2024 The Editor(s)

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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

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/d/image/242253.jpg

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https://doi.org/10.1007/978-3-031-71993-6AI-robotics; logistics; automation; warehousing; transportation; supply chains; demand forecasting; invento

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978-3-031-71992-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl

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Michael Wannenmacher,Gregor Bruggmoserrations. The traditional method of order fulfilment, where human order pickers traverse large storage areas to pick items, has become a bottleneck, consuming valuable time and resources. Robotic Mobile Fulfilment Systems (RMFS) offer a solution by using robots to transport storage racks directly to

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Endoskopische Lymphknotenchirurgieer zones, usually organized by humans in dense grids, pose a challenge for direct access to all unit loads. To access the retrieval unit load, it often becomes necessary to reshuffle blocking unit loads. When autonomous mobile robots supply production machines without human intervention, their respo

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https://doi.org/10.1007/978-3-642-84264-1, enabling them to optimize the allocation of unit loads in idle times. This work addresses the multi-robot multibay unit load pre-marshalling problem. The problem aims to reshuffle a warehouse in preparation for future demand while using multiple robots. The usage of multiple robots requires tour p

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