【摘要】 提出了一种新的基于极坐标复运算的粒子群优化算法(PSO),命名为极坐标粒子群优化算法(PPSO),并在文中进行期详细的数学描述。分别针对Schaffer’sf6构造函数和Handlod’sfH构造函数进行的PPSO算法和基本粒子群优化算法(SPSO)对比寻优测试结果表明:极坐标系和复数运算的采用、重叠空间搜索法的设计和粒子密度径周比w(RDRC)的引入,使得PPSO算法更易于稳定地、快速地、智能化地实现目标寻优。更多还原

【Abstract】 A new-style Particle Swarm Optimization (PSO) algorithm was explained based on polar coordination system and complex number operation, which was named as Polar coordination PSO (short in PPSO), and the detailed mathematic description of PPSO was also given. Taking two structuring functions of Schaffer’s f6 and Handlod’s fH as the test targets, control experiments were done with the PPSO and Simple PSO algorithm (short in SPSO) respectively, and the result shows that: owing to the application of the polar coordinate system and the complex number operation, the design of the Overlap Space Searching Method (short in OSSM), and the arrangement of the parameter of w (the Ratio of the particles Density at the Radial direction vs. that at the Circumferential way, short in RDRC), PPSO is more apt to achieve the best optimized value, and works more steadily, more quickly and more intelligently ,compared with the SPSO.更多还原