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

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書目名稱Computational Logistics影響因子(影響力)




書目名稱Computational Logistics影響因子(影響力)學(xué)科排名




書目名稱Computational Logistics網(wǎng)絡(luò)公開度




書目名稱Computational Logistics網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Computational Logistics被引頻次




書目名稱Computational Logistics被引頻次學(xué)科排名




書目名稱Computational Logistics年度引用




書目名稱Computational Logistics年度引用學(xué)科排名




書目名稱Computational Logistics讀者反饋




書目名稱Computational Logistics讀者反饋學(xué)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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