A New Algorithm for Solving Function Optimization Problem
一种求解函数优化问题的新算法

For overcoming the weakness of the population climbing evolutionary algorithm,we design a new algorithm that randomly chooses many parents from the population to recombine and the worse individuals to mutate so as to decrease the size of population, accelerate the convergence rate and improve the performance. The results of numerical experiments including seven non-linear optimization problems show that the new algorithm is characteristic of robust and high efficiency, and can quickly find the global solutions which are better than those got by MATLAB and other methods.