基于改进遗传算法的跨境电商物流智能监测预警系统的设计与实现

Fei Lei, Zicen Liao, Mingxiu Huang, Hui Tian
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引用次数: 0

摘要

跨境电商市场的快速发展导致物流复杂性增加,需要智能监控和预警系统来应对挑战。本研究的目的是设计并实现基于改进遗传算法的跨境电商物流监测预警系统,以提高运输质量的可靠性。该系统收集跨境电商物流运输质量相关数据,在一个系统中对改进遗传算法进行分析和优化,并利用改进遗传算法进行决策和规划。该系统具有实时监控功能,可发现潜在的运输质量问题,并进行预测分析,提前识别 min,及时预警。该系统可为跨境电商企业提供更高效的物流运输质量管理,降低成本,提高客户满意度。帮助企业应对物流挑战,提供更可靠的服务,促进跨境电子商务的不断发展和繁荣。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and realization of cross-border e-commerce logistics intelligent monitoring and early warning system based on improved genetic algorithm
The rapid development of the cross-border e-commerce market has led to an increase in logistics complexity, and intelligent monitoring and early warning systems are needed to meet the challenges. The objective of this study is to design and implement a cross-border e-commerce logistics monitoring and early warning system based on improved genetic algorithms to enhance the reliability of transportation quality. The system collects data related to cross-border e-commerce logistics transportation quality, analyzes and optimizes the improved genetic algorithm in one system, and uses the improved genetic algorithm for decision-making and planning. The system has a real-time monitoring function to discover potential transportation quality problems and conduct predictive analysis to identify the min advance for timely warning. The system can provide cross-border e-commerce enterprises with more efficient logistics and transportation quality management, reduce costs and improve customer satisfaction. It helps enterprises to cope with logistics challenges, provide more reliable services, and promote the continuous development and prosperity of cross-border e-commerce.
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