Particle swarm optimization (PSO) algorithm is one of the most powerful methods for solving unconstrained and constrained global optimization problems.
粒子群优化算法(PSO)是一种有效的随机全局优化技术。
Theoretical properties of the filled function are investigated, and an algorithm for constrained global optimization problem is developed from the filled function.
之后我们分析并证明了这类填充函数的性质，并依据其填充性质建立了相应的填充函数算法。
In this paper, a new auxiliary function with one parameter on box constrained for escaping the current local minimizer of global optimization problem is proposed.
本文首先对箱子约束全局最优化问题提出了一个新的辅助函数，该函数能跳出当前的局部极小点。
应用推荐