Applications of Searching Methods with Multi-Points to Constrained Optimization Problems with Complex Structure

在本项目中，粒子群优化（PSO）和差分进化（DE），这是已知的多点型优化方法的典型之一，以及多点型混沌优化方法，被选中，和变换方法（1）等式约束问题与PSO密切相关的罚函数法（2）使用PSO或DE的置换变量问题的变换方法（3）（4）粒子群优化算法在半定变量优化问题中的应用方法（5）多目标优化问题非劣解集具有较好封闭性的差分进化算法（6）粒子群优化算法在Nash均衡解中选择最优解的变换方法。另一方面，为了对PSO算法和DE算法进行分析和改进，提出了基于稳定性分析的PSO算法最佳参数设置方法，

In this project, Particle Swarm Optimization (PSO) and Differential Evolution (DE), which are known as typical ones of multi-point type optimization methods as well as a multi-point type of chaos optimization method, are picked up, and transformation meth(1)Penalty method with affinity to PSO for equality constrained problems(2)Transformation methods of problems with permutation variables to use PSO or DE(3) Transformation methods of equally constrained problems with 0-1 variables、(4)Application method of PSO for optimization problems with semi-definite variable(5)DE with better closing property to non-inferior solution set for multi-objective optimization problem(6) Transformation methods to choose a best solution among the Nash equilibrium solutions by using PSO. On the other hand, in order to try to analyze and improve concerning with PSO and DE, the best parameter setting method of PSO based on stability analy