摘要
把处理约束条件的一个外点方法和改进的粒子群优化算法相结合,提出了一种求解非线性约束优化问题的混合粒子群优化算法.该方法兼顾了粒子群优化和外点法的优点,对算法迭代过程中出现不可行粒子,利用外点法处理后产生可行粒子.数值实验表明了提出的新算法具有有效性、通用性和稳健性.
Combining an outside point method of dealing with the constraints with improved particle swarm optimization algorithm, a hybrid particle swarm optimization algorithm is proposed for solving non-linear constrained optimization problems. This method makes use of advantages of the PSO and outside point method. The non-feasible particles produced in iterative process are dealt with by the outside point method to produce feasible particles. A number of numerical experiments show that the proposed new algorithm has effectiveness and versatility and robustness.
出处
《计算数学》
CSCD
北大核心
2010年第2期135-146,共12页
Mathematica Numerica Sinica
基金
国家自然科学基金项目资助(60962006)
宁夏自然科学基金项目资助(NZ0848)
关键词
全局最优化
非线性约束优化
粒子群优化
外点法
global optimization
non-linear constrained optimization
particle swarm optimization （PSO）
outside point method
