资源简介
基于遗传算法的电力系统无功优化程序,可以帮您更好的进行电力系统的优化,使用标准的MATLAB程序
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代码片段和文件信息
function [bestmembestvalnfeval] = devec3(fnameVTRDXVminXVmaxyNPitermaxFCRstrategyrefresh);
% minimization of a user-supplied function with respect to x(1:D)
% using the differential evolution (DE) algorithm of Rainer Storn
% (http://www.icsi.berkeley.edu/~storn/code.html)
%
% Special thanks go to Ken Price (kprice@solano.community.net) and
% Arnold Neumaier (http://solon.cma.univie.ac.at/~neum/) for their
% valuable contributions to improve the code.
%
% Strategies with exponential crossover further input variable
% tests and arbitrary function name implemented by Jim Van Zandt
% 12/97.
%
% Output arguments:
% ----------------
% bestmem parameter vector with best solution
% bestval best objective function value
% nfeval number of function evaluations
%
% Input arguments:
% ---------------
%
% fname string naming a function f(xy) to minimize
% VTR “Value To Reach“. devec3 will stop its minimization
% if either the maximum number of iterations “itermax“
% is reached or the best parameter vector “bestmem“
% has found a value f(bestmemy) <= VTR.
% D number of parameters of the objective function
% XVmin vector of lower bounds XVmin(1) ... XVmin(D)
% of initial population
% *** note: these are not bound constraints!! ***
% XVmax vector of upper bounds XVmax(1) ... XVmax(D)
% of initial population
% y problem data vector (must remain fixed during the
% minimization)
% NP number of population members
% itermax maximum number of iterations (generations)
% F DE-stepsize F from interval [0 2]
% CR crossover probability constant from interval [0 1]
% strategy 1 --> DE/best/1/exp 6 --> DE/best/1/bin
% 2 --> DE/rand/1/exp 7 --> DE/rand/1/bin
% 3 --> DE/rand-to-best/1/exp 8 --> DE/rand-to-best/1/bin
% 4 --> DE/best/2/exp 9 --> DE/best/2/bin
% 5 --> DE/rand/2/exp else DE/rand/2/bin
% Experiments suggest that /bin likes to have a slightly
% larger CR than /exp.
% refresh intermediate output will be produced after “refresh“
% iterations. No intermediate output will be produced
% if refresh is < 1
%
% The first four arguments are essential (though they have
% default values too). In particular the algorithm seems to
% work well only if [XVminXVmax] covers the region where the
% global minimum is expected. DE is also somewhat sensitive to
% the choice of the stepsize F. A good initial guess is to
% choose F from interval [0.5 1] e.g. 0.8. CR the crossover
% probability constant from interval [0 1] helps to maintain
% the diversity of the population and is rather
属性 大小 日期 时间 名称
----------- --------- ---------- ----- ----
文件 13663 2006-04-16 06:41 基于遗传算法matlab优化程序\devec3.m
文件 428 2006-04-16 06:42 基于遗传算法matlab优化程序\rosen.m
文件 1691 2006-04-16 06:42 基于遗传算法matlab优化程序\run1.m
文件 784 2006-04-16 06:42 基于遗传算法matlab优化程序\run2.m
文件 5825 2006-04-16 06:42 基于遗传算法matlab优化程序\yue.m
文件 5797 2010-04-08 21:32 基于遗传算法matlab优化程序\yue2.m
目录 0 2010-04-14 13:35 基于遗传算法matlab优化程序
----------- --------- ---------- ----- ----
28188 7
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