Dynamic modeling and structural optimization of multi-accessory value network based on complex networks

Value chain analysis identifies key value-adding activities and guides supply chain design and optimization. However, existing research provides limited systematic analysis of the dynamic evolution, collaborative evaluation, and structural optimization of chain-network dual structures. This study develops an integrated framework for multi-accessory value networks in distributed manufacturing. First, a dynamic model based on complex network theory integrates multiple node types and edge attributes. Association rules identify potential cooperation relationships, while direct and potential cooperation edges are updated across consecutive observation periods using observed business data. Second, a multidimensional evaluation system comprising collaborative compactness, collaborative density, and collaboration rate quantifies structural efficiency using the global clustering coefficient and network density. Finally, an optimization model using the Non-dominated Sorting Genetic Algorithm II dynamically adjusts the edge set to improve collaborative efficiency, total value added, and connectivity scale, providing theoretical support and practical pathways for the intelligent upgrading of industrial value chains.