关键词: 产业链金融, 0-1背包策略, 离散粒子群优化算法, 风险承受力, 融资效率

Abstract: To solve the complex and diverse matching problems between enterprises financial products in the industrial chain,an improved discrete particle swarm optimization algorithm based on 0-1 knapsack strategy was proposed from the perspective of risk tolerance and financing efficiency for solving the bilateral matching model.The objective function was constructed aiming at the minimum risk tolerance requirement of enterprise and the highest financing efficiency of financial products.The highest preference sequence information was used to calculate the bilateral match main body satisfaction,and the bilateral matching optimization model which was calculated by improved discrete particle swarm algorithm was built.The updated iterative calculation way of particle swarm velocity and displacement were simplified by this method,the algorithm redundancy was reduced efficiently,and the solution convergence speed and precision of the model were improved.The new energy automobile industry chain was used to verify the calculation speed and searching ability of the algorithm,and the result showed that the operation speed and the searching ability of the improved algorithm was proved greatly by compared with the traditional algorithm,and the defects of premature convergence and slow convergence speed were avoided.

Key words: industry chain finance, 0-1 knapsack strategy, discrete particle swarm optimization algorithm, risk bearing capacity, financing efficiency