面向区块链的协同业务建模及其并行优化算法

In response to challenges encountered in supply chain management such as collaborative efficiency, information traceability, and trust crises, a parallel computing model, PNSGA-HI, is introduced to tackle the multifaceted issues in blockchain. Initially, by exploring the interactions among blockchain, the blockchain lead enterprises(BLEs), and blockchain on-chain enterprises (BOEs), parameters such as costs for BLEs, service points, the number of participating BOEs, and blockchain stability are transformed into a multi-level multi-business collaborative model. Subsequently, to enhance the efficiency of the genetic algorithm in generating offspring cache areas, the crossover and mutation components are processed in parallel, leading to a substantial reduction in the model's solution time. Furthermore, to handle the challenge of non-mutually dominant Pareto solutions, TOPSIS is employed to calculate the Euclidean distance and determine the optimal solutions. Finally, the effectiveness of the proposed model is verified through 10 sets of simulation experiments. The results indicate that the computation time of PNSGA- III is 16. 37% shorter than that of non-parallel algorithms. The conflicting constraint mechanism of blockchain provides a wider range of options, enhancing its adaptability to complex requirements. Under dynamic task flows, the service points of the optimized S8 solution are 45% higher than those of the unoptimized solution. This research provides fresh insights and tools for advancing supply chain management practices.