The green modern digital intelligent supply chain system is facing constantly changing demands and complex environments in practice, which is of great significance for the iterative upgrade algorithm design of the system. This study aims to propose a design method for the optimal iterative upgrade algorithm of a green modern digital intelligent supply chain system, in order to promote the efficient operation and sustainable development of the supply chain system. Firstly, through comprehensive analysis of various links in the logarithmic intelligent supply chain system, optimization objectives and constraints are determined. Then, based on genetic algorithm, design the optimal iterative upgrade algorithm model for the digital intelligent supply chain system, and optimize the solution space through repeated iterations to find the optimal solution. Finally, the effectiveness and feasibility of the proposed algorithm were verified through simulation experiments. The results of this study will provide decision support for enterprises in designing and optimizing digital intelligence supply chain systems, promoting efficient resource utilization.
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Tian et al. (2024) studied this question.
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