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Development Of Rfid-based Reverse Logistics System

机译：基于RFID的逆向物流系统的开发

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摘要

Reverse logistics, which is the management or return flow due to product recovery, goods return, or overstock, form a closed-loop supply chain. The success of the closed-loop supply chain depends on actions of both manufacturers and customers. Now, manufacturers require producing products which are easy for disassembly, reuse and remanufacturing owing to the law of environmental protection. On the other hand, the number of customers supporting environmental protection by delivering their used products to collection points is increasing. According to the findings, the total cost spent in reverse logistics is huge. In order to minimize the total reverse logistics cost and high utilization rate of collection points, selecting appropriate locations for collection points is critical in reverse logistics. This paper proposes a genetic algorithm to determine such locations in order to maximize the coverage of customers. Also, the use of RF1D is suggested to count the quantities of collected items in collection points and send the signal to the central return center. This can facilitate the vehicle scheduling for transferring the items from collection points to the return center. The significance of this research is the proposal of RFID-based reverse logistics framework and optimization of locations of collection points which allow economically and ecologically reasonable recycling. Simulation results indicated that the genetic algorithm is able to produce good-quality solutions in terms of coverage of collection points by choosing suitable locations for collection points and RFID can help detect the quantity of returned products so as to increase efficiency of logistics operations.
机译：逆向物流，即由于产品回收，退货或积压库存导致的管理或回流，形成了一个闭环供应链。闭环供应链的成功取决于制造商和客户的行动。现在，由于环境保护法，制造商要求生产易于拆卸，重复使用和再制造的产品。另一方面，通过将用过的产品运送到收集点来支持环境保护的客户数量在增加。根据调查结果，逆向物流的总成本巨大。为了最大程度地减少逆向物流的总成本和收集点的高利用率，为逆向物流选择合适的收集点位置至关重要。本文提出了一种遗传算法来确定此类位置，以最大程度地覆盖客户。另外，建议使用RF1D对收集点中的收集物品进行计数，并将信号发送到中央返回中心。这可以促进车辆调度以将物品从收集点转移到返回中心。这项研究的意义在于提出了基于RFID的逆向物流框架并优化了收集点的位置，从而实现了经济和生态上的合理回收。仿真结果表明，该遗传算法能够通过选择合适的收集点位置，在收集点覆盖范围内产生高质量的解决方案，RFID可以帮助检测退货数量，从而提高物流效率。

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