Order Picking System Optimization Based on Picker-Robot Collaboration

Yang Zou, Dongxue Zhang, Mingyao Qi
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引用次数: 3

Abstract

Distribution centers of E-commerce companies have been under pressure as a result of the development of the Internet and E-commerce technologies. Therefore, the improvement of order picking efficiency and the reduction of logistics cost rely on the optimization of order picking in distribution centers. In this paper, a picker-robot collaboration order picking system has been proposed. The human pickers are assigned to different zones, while the automated guided vehicles (AGVs) pick the orders from different zones. To optimize the collaboration scheme, the mathematical model together with a two-stage heuristic algorithm is proposed to solve the problems, including order batching, AGV routing and zone scheduling. The case study results have shown the effectiveness and the computation efficiency of the proposed two-stage heuristic algorithm.
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基于机器人协同的拣货系统优化
随着互联网和电子商务技术的发展,电子商务企业的配送中心面临着巨大的压力。因此,提高拣货效率,降低物流成本,有赖于对配送中心拣货的优化。提出了一种拣货机器人协同拣货系统。人工拾取者被分配到不同的区域,而自动导引车(agv)从不同的区域拾取订单。为了优化协同方案,提出了数学模型和两阶段启发式算法,解决了订单批处理、AGV路由和区域调度等问题。实例研究结果表明了所提出的两阶段启发式算法的有效性和计算效率。
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