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Reinforcement-Learning-Based Local Search Approach to Integrated Order Batching: Driving Growth for Logistics and Retail

June 27, 2023 by LiJie Zhou

As an important part of Industry 4.0, a smart warehouse can offer smart tips and operational constraints for users. Improving its work efficiency is a promising growth driver for logistics companies and retailers. Therefore, a reinforcement-learning-based adaptive iterated local search (RAILS) approach is proposed to improve order-picking efficiency for a smart warehouse. A … [Read more...] about Reinforcement-Learning-Based Local Search Approach to Integrated Order Batching: Driving Growth for Logistics and Retail

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IEEE Robotics & Automation Magazine (RAM) has over 14,000 readers who are the people who drive this remarkable technology. More than half work in basic research and many of the others are top level engineers and decision-makers in industry.  This magazine highlights new concepts in Robotics and Automation that are applied to real-world systems. It delivers tutorial and survey papers by distinguished experts in the field, organizes focused special issues on hot topics, and provides a forum for disseminating and discussing emerging trends, novel achievements, and selected news relevant to the development of the whole community active in these fields worldwide.

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IEEE Robotics & Automation Magazine  publishes four issues per year: March, June, September and December.