Optimization Decision Promotion Model of Supply Chain Networks with Logistics Speed

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Abstract:

Commercial logistics speed has the dynamic characteristics of the impact on supply chain. In order to establish the relationship between logistics speed and supply chain network decision model, accurately grasp the logistics effect on supply chain decision, an optimization decision model of supply chain networks with logistics layer weighting was proposed. The whole complex network model of hierarchical supply chain was established. The product pricing and logistics strategies and optimization decision were proposed for realizing the maximum total profit. The simulation results show that the optimal decision model is shown in small world property, and it can reflect the product consumption demand reality effectively, the total profit of the whole supply chain is significantly increased compared with the traditional method, and the network system is adaptive and robust.

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6170-6173

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September 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] XIE Xiaolan, LIU Liang, CAO Yingzhong. Trust model based on feedback evaluation in cloud manufacturing environment [J]. Advanced Materials Research, 2011, 308-310: 1740-1745.

DOI: 10.4028/www.scientific.net/amr.308-310.1740

Google Scholar

[2] PAULO ÁVILA, ALZIRA MOTA, ANTÓNIO PIRES, et al. Supplier's Selection Model based on an Empirical Study[J]. Procedia Technology, 2012, 5: 625-634.

DOI: 10.1016/j.protcy.2012.09.069

Google Scholar

[3] LEI WANG, MENGXING HUANG, XIANGLONG YE, et al. A Reference Architecture of Supply Chain Based on Cloud Computing and Its Model Analysis[C]/In Proceedings of the 2012 3rd International Conference on E-Business and E-Government. Washington, DC: IEEE Computer Society, 2012, 05: 40-43.

Google Scholar

[4] GUO Qiu-xia, DENG Xiang-ming, OU Yang-jiang. Evaluation of Value Chain Risks Based on BP Artificial Neural Network[J]. Logistics Technology, 2011, 30(7): 120-122.

Google Scholar

[5] MA Jian- hong, JI Li- xia. Study on Agent Immune Network Monitoring System Model[J]. Computer Simulation, 2013, 30(5): 213-216.

Google Scholar

[6] Shen Yuan. Research on Intrusion Detection System Neural Networks and Principal Component Analysis[J]. Bulletin of Science and Technology, 2013, 29(6): 32-34.

Google Scholar