摘要
For overcoming the weakness of the population climbing evolutionary algorithm,we design a new algorithmthat randomly chooses many parents from the population to recombine and the worse individuals to mutate so as to de-crease the size of population, accelerate the convergence rate and improve the performance. The results of numericalexperiments including seven non-linear optimization problems show that the new algorithm is characteristic of robustand high efficiency,and can quickly find the global solutions which are better than those got by MATLAB and othermethods.
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.
出处
《计算机科学》
CSCD
北大核心
2003年第1期80-81,69,共3页
Computer Science
基金
国家自然科学基金(编号:60133010
60073043
70671042)
