阿里巴巴车辆路线算法实现快速取货

Haoyuan Hu, Ying Zhang, Jiangwen Wei, Yang Zhan, Xinhui Zhang, Shaojian Huang, Guangrui Ma, Yuming Deng, Siwei Jiang
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引用次数: 7

摘要

阿里巴巴集团开创了线上线下一体化零售模式,允许客户在其参与的商店或餐馆在线订购电子商务和杂货产品,并在某些情况下在下单后30分钟内快速送达。为了满足这些服务承诺,必须做出快速的在线路线决策,以优化仓库的拣货路线和司机的送货路线。由于严格的服务承诺、不确定性和空间有限的仓库中的复杂操作,这些路由问题的解决方案变得复杂。阿里巴巴开发了一套解决车辆路线问题(vrp)的算法,其中包括一个开放架构的自适应大社区搜索,以支持解决各种路线问题,以及一种基于深度学习的方法,该方法可以离线训练神经网络模型,以在线生成几乎即时的解决方案。这些算法已经在阿里巴巴的几个子公司中被用于解决vrp,每年节省了超过5000万美元的资金,并适用于更广泛的物流行业。这些算法的成功,在阿里巴巴内部发酵了一个运筹学的内源社区,提升了公司高管对运筹学的信心,使运筹学成为阿里巴巴集团的核心竞争力之一。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Alibaba Vehicle Routing Algorithms Enable Rapid Pick and Delivery
Alibaba Group pioneered integrated online and offline retail models to allow customers to place online orders of e-commerce and grocery products at its participating stores or restaurants for rapid delivery—in some cases, in as little as 30 minutes after an order has been placed. To meet these service commitments, quick online routing decisions must be made to optimize order picking routes at warehouses and delivery routes for drivers. The solutions to these routing problems are complicated by stringent service commitments, uncertainties, and complex operations in warehouses with limited space. Alibaba has developed a set of algorithms for vehicle routing problems (VRPs), which include an open-architecture adaptive large neighborhood search to support the solution of variants of routing problems and a deep learning-based approach that trains neural network models offline to generate almost instantaneous solutions online. These algorithms have been implemented to solve VRPs in several Alibaba subsidiaries, have generated more than $50 million in annual financial savings, and are applicable to the broader logistics industry. The success of these algorithms has fermented an inner-source community of operations researchers within Alibaba, boosted the confidence of the company’s executives in operations research, and made operations research one of the core competencies of Alibaba Group.
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