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Equilibrium Scheduling of Dynamic Supply Chain Network Resources Under Carbon Tax Policy

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Advanced Hybrid Information Processing (ADHIP 2023)

Abstract

The supply chain network is usually composed of multiple nodes and paths, and the energy consumption and carbon emissions of each node will change, leading to dynamic changes in the network structure and resource demand. In order to improve the utilization rate and accuracy of dynamic supply chain network resource balanced scheduling, under the current carbon tax policy, a comprehensive study on dynamic supply chain network resource balanced scheduling was carried out. Firstly, the RSUC dynamic supply chain network model is constructed to reflect the operation changes of the dynamic supply chain network under the carbon tax policy in real time through the iterative operation of the model. Secondly, a multi-path link routing algorithm for dynamic supply chain network resource balanced scheduling is designed, and the one with the highest success rate is selected as the transmission path for dynamic supply chain network resource balanced scheduling. Calculate the use of resources in dynamic supply chain network nodes, obtain the use and surplus of dynamic supply chain network resources under the carbon tax policy, and make every node’s resources be used as far as possible. On this basis, according to the actual situation and characteristics of the supply chain network operation, the dynamic quota of network resource balanced scheduling is designed in an all-round way, so as to achieve the goal of dynamic supply chain network resource balanced scheduling under the carbon tax policy. Experimental analysis shows that after the application of the new method, the network resource utilization rate is high under different network workload data segments.

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Correspondence to Hao Zhu .

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© 2024 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zhu, H. (2024). Equilibrium Scheduling of Dynamic Supply Chain Network Resources Under Carbon Tax Policy. In: Yun, L., Han, J., Han, Y. (eds) Advanced Hybrid Information Processing. ADHIP 2023. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 549. Springer, Cham. https://doi.org/10.1007/978-3-031-50549-2_27

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  • DOI: https://doi.org/10.1007/978-3-031-50549-2_27

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-50548-5

  • Online ISBN: 978-3-031-50549-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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