Paper
22 April 2022 Research and analysis of supplier selection and enterprise maximum production capacity based on simulated annealing and BP neural network model
Hong-yu Zhu, Shu-bo Chang, Xiao-yu Chen, Jie-ran Mao, Li-wen Zhang, Shuai-feng Li
Author Affiliations +
Proceedings Volume 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021); 1216329 (2022) https://doi.org/10.1117/12.2627988
Event: International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 2021, Nanjing, China
Abstract
Regarding the manufacturer's decision problem in selecting suppliers and carriers, this paper uses the grey comprehensive evaluation method to evaluate the importance of suppliers. Then, a simulated annealing algorithm is used to optimize the supplier selection and determine the weight of supplier selection. In addition, the neural network BP is used to build a model to predict the production capacity of the enterprise, and a nonlinear programming model is built to solve multiple objectives, such as large supply, low transportation loss rate, high delivery fulfillment rate, and small production. According to the differences in the supply chain, the problem is solved using MATLAB software; and finally the company's strategy for selecting suppliers and carriers in the future is given.
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Hong-yu Zhu, Shu-bo Chang, Xiao-yu Chen, Jie-ran Mao, Li-wen Zhang, and Shuai-feng Li "Research and analysis of supplier selection and enterprise maximum production capacity based on simulated annealing and BP neural network model", Proc. SPIE 12163, International Conference on Statistics, Applied Mathematics, and Computing Science (CSAMCS 2021), 1216329 (22 April 2022); https://doi.org/10.1117/12.2627988
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KEYWORDS
Brain

Neurons

Data processing

Neural networks

Algorithms

Analytical research

Annealing

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