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将粒子群算法用于5片镜光学系统的设计优化中。由球差、像距、畸变、场曲、彗差和光线弥散值构成光学评价函数，用这个评价函数作为粒子群算法的适应度函数，优化设计了一结构简单的5片镜系统，并把此5片镜系统与ZEBASE中5片镜系统的球差、畸变、子午场曲、弧矢场曲、子午光线弥散值、弧矢光线弥散值、子午彗差、弧矢彗差进行了对比。对比结果显示，用粒子群算法设计的5片镜系统的球差、畸变、子午场曲、弧矢场曲、弧矢光线弥散值较小，ZEBASE中五片镜系统的子午光线弥散值、子午彗差、弧矢彗差较小。设计实例表明，粒子群算法可以克服现有光学设计软件高度依赖具体初始结构的缺点，可以自由控制结构参数的搜索范围，从而提高光学系统设计的智能化程度。“,”Particle swarm optimization (PSO) technique is applied to design a five-lens system. The optical merit function composed of spherical aberrations, an image distance, distortions, field curvatures, comas and light dispersion values, were employed as fitness functions of the particle swarm algorithm. By using this function automatic searching for the optimal design, a simple five-lens system was carried out. Comparisons in terms of spherical aberrations, distortions, field curvatures, comas and light dispersion values were performed between a five-lens system designed with PSO and a five-lens system from ZEBASE. The result shows that spherical aberrations, distortions, meridional field curvatures, sagittal field curvatures, sagittal light dispersion values of a five-lens system designed with PSO are smaller, and meridional light dispersion values, meridional comas, sagittal comas of a five-lens system from ZEBASE are smaller. The example for a five-lens system design using particle swarm algorithm indicates that PSO can overcome the shortcomings of the modern optical design software which highly depends on an initial structure input by the user and can create arbitrarily search ranges of structure parameters, which is an important step towards automatic design with artificial intelligence.