针对现有遗传算法在多维非线性优选方面的不足，本文提出了一种基于小生境进化算法（NEA）的非线性优选模型，探讨了NEA算法的参数选择原则。通过大量仿真和比较，表明...

针对现有遗传算法在多维非线性优选方面的不足，本文提出了一种基于小生境进化算法（NEA）的非线性优选模型，探讨了NEA算法的参数选择原则。通过大量仿真和比较，表明算法在复杂非线性优选中具有快速、高效、鲁棒性强的特点，并能在全局范围内有效搜索所有最优解。 -against existing genetic algorithms in three-dimensional nonlinear optimization for the shortage, the paper presents a niche evolutionary algorithm (NEA) nonlinear optimization model, the NEA on the parameters chosen algorithm principle. Through simulation and large, the algorithm shown in a complex nonlinear optimization is fast, efficient, robust features of the strong, and the global scope effective search all the optimal solution.

Debug
EP.APS
EP.clw
EP.cpp
EP.dsp
EP.dsw
EP.h
EP.ncb
EP.opt
EP.rc
EP2bestResult.txt
EP2Result.txt
EPDlg.cpp
EPDlg.h
example2.txt
ReadMe.txt
res
EP.ico
EP.rc2
resource.h
Result_30var-32success.txt
Result_30var-32success2.txt
Result_30var-32success3.txt
Result_30var1001-19.txt
Result_30var1001-31.txt
Result_30var1001.txt
Result_onevar.txt
Result_threevar.txt
StdAfx.cpp
StdAfx.h