Evaluating and Optimizing Supply Chains with LMBP Algorithm
Meng Hu1,2, Liang Xiaobei1, Yang Yixiong2,3, Li Min2,3()
1School of Economics and Management, Tongji University, Shanghai 200092, China 2College of Fashion and Design, Donghua University, Shanghai 200051, China 3Shanghai Institute of Design and Innovation, Tongji University, Shanghai 200092, China
[Objective] This paper uses the LMBP algorithm of feedback neural network to evaluate and optimize the supply chains, aiming to improve the decision-making of enterprises. [Methods] First, we built an evaluation model for supply chains. Then, we generated 21 indicators for corporate performance based on this model. Third, we used the MATLAB to evaluate this algorithm. [Results] The proposed method helped enterprises obtain the results of performance analysis in time, and then improved the management of procurement, inventory, and sales. It reduced the operation costs of enterprises, and improved the decision making process. [Limitations] The new method should be examined with more cases. [Conclusions] The proposed method could improve the performance of supply chains.
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