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Perishable Goods Supply Chain Network Planning on E-commerce Platforms Based on Improved Sparrow Search Algorithm
With the change in consumption patterns, purchasing perishable products on e-commerce platforms has become a new way of consumption. Traditional perishable goods supply chain planning methods have problems such as large scale and long solving time. In response to these issues, a Tent chaotic map is proposed to improve the local optimal problem in the sparrow search algorithm. The improved method is applied to optimize the perishable goods supply chain network planning model on e-commerce platforms. To verify the performance, comparative experiments are conducted. According to the findings, the precision of the improved algorithm is 92%, the accuracy is 97%, and the F-value is 0.92, all of which are better than the comparative algorithm. Subsequently, the actual application effect of the improved model is verified. The customer satisfaction loss value is stable at 0.1408. The total cost deviation value is stable at 0.434. The running time and error of the model are 9 s and 6%, respectively, which are better than the comparative models. In summary, the proposed e-commerce platform perishable goods supply chain network planning model based on the improved sparrow search algorithm has high accuracy and fast work efficiency, achieving optimization of perishable goods supply chain network planning.
Perishable Goods Supply Chain Network Planning on E-commerce Platforms Based on Improved Sparrow Search Algorithm
With the change in consumption patterns, purchasing perishable products on e-commerce platforms has become a new way of consumption. Traditional perishable goods supply chain planning methods have problems such as large scale and long solving time. In response to these issues, a Tent chaotic map is proposed to improve the local optimal problem in the sparrow search algorithm. The improved method is applied to optimize the perishable goods supply chain network planning model on e-commerce platforms. To verify the performance, comparative experiments are conducted. According to the findings, the precision of the improved algorithm is 92%, the accuracy is 97%, and the F-value is 0.92, all of which are better than the comparative algorithm. Subsequently, the actual application effect of the improved model is verified. The customer satisfaction loss value is stable at 0.1408. The total cost deviation value is stable at 0.434. The running time and error of the model are 9 s and 6%, respectively, which are better than the comparative models. In summary, the proposed e-commerce platform perishable goods supply chain network planning model based on the improved sparrow search algorithm has high accuracy and fast work efficiency, achieving optimization of perishable goods supply chain network planning.
Perishable Goods Supply Chain Network Planning on E-commerce Platforms Based on Improved Sparrow Search Algorithm
J. Inst. Eng. India Ser. C
Ma, Xiaoqian (author) / Luo, Fang (author)
Journal of The Institution of Engineers (India): Series C ; 106 ; 353-365
2025-02-01
13 pages
Article (Journal)
Electronic Resource
English
E-commerce platform , Perishable goods supply chain , SSA algorithm , Tent chaotic mapping Commerce, Management, Tourism and Services , Business and Management , Information and Computing Sciences , Artificial Intelligence and Image Processing , Engineering , Aerospace Technology and Astronautics , Mechanical Engineering , Industrial and Production Engineering
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