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IoT-enabled Dynamic Optimisation for Sustainable Reverse Logistics

机译:基于物联网的动态优化实现可持续逆向物流

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Currently, typical challenges that logistics industry faces include the exploding logistics (including reverse logistics) tasks, the lack of real-time and accurate logistics information, and demands towards sustainable logistics. Therefore, it is difficult for logistic companies to achieve highly-efficient and sustainable reverse logistics. This paper adopts a bottom-up logistics strategy that aims to achieve the real-time information-driven dynamic optimisation distribution for logistics tasks. Under this strategic framework, an IoT-enabled real-time information sensing model is designed to sense and capture the real-time data of logistics resources, which are shared among companies after the value-added processes. Real-time information-driven dynamic optimisation for logistics tasks is proposed to optimise the configuration of logistics resources, reduce logistics cost, energy consumption and the distribution distance, and alleviate the environmental pollution. The objective of this research is to develop an innovative logistics distribution model for sustainable logistics.
机译:当前,物流业面临的典型挑战包括爆炸性的物流(包括反向物流)任务,缺乏实时和准确的物流信息以及对可持续物流的需求。因此,物流公司很难实现高效且可持续的逆向物流。本文采用了一种自下而上的物流策略,旨在实现物流任务实时信息驱动的动态优化分配。在此战略框架下,设计了一种基于IoT的实时信息感知模型,以感知和捕获物流资源的实时数据,这些数据在增值过程后在公司之间共享。提出了基于实时信息驱动的物流任务动态优化算法,以优化物流资源配置,降低物流成本,能耗和配送距离,减轻环境污染。这项研究的目的是为可持续物流开发一种创新的物流配送模型。

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