Developments of Multiple Points Coupling Type of Global Optimization Methods with Adaptability and Robustness by Mechanisms of Diversification and Intensification

为了实现优化搜索的多样化和集约化机制，以提供对各种结构的适应性和对问题规模的鲁棒性，发展了新型的多搜索点全局优化算法，改进了现有的多搜索点方法如粒子群优化（PSO），并提出了扩大已发展方法机理的杂交方法。此外，通过许多全局优化的基准问题以及控制系统设计的应用，证明了所开发的，改进的和建议的方法的搜索能力。

In order to realize mechanisms of diversification and intensification in search for an optimal solution as strategies to provide adaptability to various structures and robustness against the problem scale, the new type of global optimization algorithms by multiple search points are developed, the existing multiple search point methods such as Particle Swarm Optimization (PSO) are improved, and hybridization methods to enlarge the mechanisms of developed method are proposed. Moreover, the searching abilities of the developed, improved and proposed methods are certified through many benchmark problems for global optimization as well as applications to designing of control systems.