Supply Chain Management Using Bee Swarm Optimisation to Improve the Logistics in E- Commerce Era

N. Bindu Madhavi, G. Kannan, K. Vinayagam, M. Jayaprakash
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Abstract

The traditional supply chain management and logistics aims at delivering the shipments to user end without delay. The research provides directions for the supply chain management to improve the chain of logistics for the ecommerce sites using nature inspired bee swarm optimization. The utilization of the nature inspired model improves the decision-making ability of the supply chain logistics using various input parameters. The simulation is tested with the development of supply and track model in python tool that uses bee swarm intelligence to track the logistics chain and thereby mitigating the delay in delivering the shipments to the user end. The results show that the proposed intelligence model achieves a higher tracking efficiency than the existing SOTA.
利用蜂群优化改进电子商务时代的供应链管理
传统的供应链管理和物流的目标是将货物及时地送到用户端。本研究为电子商务网站供应链管理提供了利用自然启发的蜂群优化来改善物流链的方向。利用自然启发模型,提高了使用多种输入参数的供应链物流决策能力。利用python工具开发的供应和跟踪模型对仿真进行了测试,该模型利用蜂群智能跟踪物流链,从而减少了向用户端交付货物的延迟。结果表明,该智能模型比现有的SOTA具有更高的跟踪效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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