资 源 简 介
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.
文 件 列 表
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
