在马克维茨投资组合的均值-方差模型框架下,给出限制投资数量的自融资投资组合优化模型.在金融市场上有广泛应用,为了有效地求解此类问题的最优解,采用一种基于广义学习策略的约束粒子群算法(CPSO).CPSO算法具有广义的学习策略,极大地提升了种群的多样性,进而提升种群跳出局部最优解的能力.在基准函数测试中,结果显示CPSO算法有较好的运行结果.在自融资投资组合优化模型上,优化结果表明CPSO算法是可行的,有效的,并有较好的优化结果. Under the framework of Mean-Variance model of Markowitz’s portfolio, a self-financing investment portfolio optimization model is proposed to limit the number of investments, which is widely used in the financial markets. In order to solve the optimal solution of such problems effectively, Constrained Particle Swarm Optimization (CPSO) based on generalized learning strategy.CPSO algorithm has a broad learning strategy, which greatly improves the diversity of the population and enhances the ability of the population to jump out of the local optimal solution.In the benchmark function test, the results show that the CPSO The algorithm has good running results.On the optimization model of self-financing investment portfolio, the optimization results show that the CPSO algorithm is feasible, effective and has better optimization results.