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5 August 2024 Design and simulation of intelligent cross-border e-commerce logistics pathway system for intelligent manufacturing enterprises based on improved genetic algorithm
Na Yao, Xiaojuan Chen, Fei Lei
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Proceedings Volume 13226, Third International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2024); 1322654 (2024) https://doi.org/10.1117/12.3038284
Event: 3rd International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2024), 2024, Changsha, China
Abstract
The system aims to optimize the logistics pathway for cross-border e-commerce by integrating intelligent technologies and leveraging an improved genetic algorithm. The proposed system utilizes intelligent manufacturing technologies, such as Internet of Things (IoT) devices and artificial intelligence, to collect and analyze real-time data from various sources, including suppliers, manufacturers, and customers. The system then uses an improved genetic algorithm to generate optimized logistics pathways that minimize transportation costs and delivery time while maximizing customer satisfaction. The improved genetic algorithm incorporates a fitness function that considers multiple factors, including transportation costs, delivery time, customer feedback, and supplier reliability. Overall, the design and simulation of the intelligent cross-border e-commerce logistics pathway system presented in this paper offer a promising solution for intelligent manufacturing enterprises to optimize their logistics operations and enhance their competitiveness in the global market. The system’s ability to leverage intelligent technologies and the improved genetic algorithm enables it to adapt to changing conditions and continuously improve its performance.
(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.
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Na Yao, Xiaojuan Chen, and Fei Lei "Design and simulation of intelligent cross-border e-commerce logistics pathway system for intelligent manufacturing enterprises based on improved genetic algorithm", Proc. SPIE 13226, Third International Conference on Advanced Manufacturing Technology and Manufacturing Systems (ICAMTMS 2024), 1322654 (5 August 2024); https://doi.org/10.1117/12.3038284
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KEYWORDS
Genetic algorithms
Intelligence systems
Manufacturing
Design
Computer simulations
Mathematical optimization
Computer security
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