文件列表:

zhangbingGA\Code.asv (1007, 2009-03-10)
zhangbingGA\Code.m (1088, 2009-03-11)
zhangbingGA\Cross.asv (3772, 2009-03-10)
zhangbingGA\Cross.m (4033, 2009-03-11)
zhangbingGA\Decode.m (953, 2003-07-16)
zhangbingGA\fun.asv (8862, 2009-03-11)
zhangbingGA\fun.m (8864, 2009-03-11)
zhangbingGA\fx.m (48, 2009-03-09)
zhangbingGA\Genetic.asv (4717, 2009-03-11)
zhangbingGA\Genetic.m (4828, 2009-03-11)
zhangbingGA\Mutation.m (2448, 2009-03-11)
zhangbingGA\PHI.asv (95, 2009-03-09)
zhangbingGA\PHI.m (95, 2009-03-09)
zhangbingGA\Select.m (1502, 2003-07-26)
zhangbingGA\shujujiefangcheng.nb (10404, 2009-03-10)
zhangbingGA\test.m (76, 2009-03-11)
zhangbingGA\testAimFunc.m (108, 2009-03-05)
zhangbingGA\tiaojian.asv (909, 2009-03-11)
zhangbingGA\tiaojian.m (921, 2009-03-11)
zhangbingGA\解方程.txt (1988, 2009-03-09)
zhangbingGA (0, 2009-03-11)

SGA（Simple Genetic Algorithm）是一种强大的智能多变量优化算法，它模仿种群繁殖规律来进行 优化。 本SGA可以优化变量，求最小值,最大值（当把函数倒数也就求最小值啦） 并且支持浮点编码，grey编码，二进制编码；轮赌法选择，锦标赛选择；单点交叉，均布交叉，浮点交叉； 单点变异，浮点变异； 调用时 Genetic（目标函数名） if you get some problems,you can email to me shoppingxo@hotmail.com qq:10901831 Xi Huabin（席华彬） 使用环境：MATLAB6.5+ToolBox 使用SGA时， 首先需要一个目标函数（像AimFunc.m），该函数返回适应度 输入变量为待优化变量x 输出为一个适应度。 然后 修改Genetic.m中可以修改的地方 例一 maxgen=200; % maximum generation sizepop=100; % size of population AimFunc=StrAimFunc; % this is function of counting fitness fselect='tournament'; % method of select % you can choose 'tournament';'roulette' fcode='float'; % method of coding % you can choose 'float';'grey';'binary' pcross=[0.6]; % probablity of crossover,between 0 and 1 fcross='float'; % method of crossover % you can choose 'float';'simple';'uniform' pmutation=[0.2]; % probability of mutation,between 0 and 1 fmutation='float'; % method of mutation % you can choose 'float';'simple'; lenchrom=[1 1 1 1 1]; % length of bit of every varible bound=[0 1;... 0 1;... 0 1;... 0 1;... 0 1]; 选择了浮点编码，tournament选择，浮点交叉，浮点变异。 注：采用浮点编码时，以后的交叉，变异只能是浮点，且lenchrom向量中都为1，向量长度为待优化变量个数。 bound为各个变量的范围 例二 maxgen=200; % maximum generation sizepop=100; % size of population AimFunc=StrAimFunc; % this is function of counting fitness fselect='tournament'; % method of select % you can choose 'tournament';'roulette' fcode='binary'; % method of coding % you can choose 'float';'grey';'binary' pcross=[0.6]; % probablity of crossover,between 0 and 1 fcross='uniform'; % method of crossover % you can choose 'float';'simple';'uniform' pmutation=[0.2]; % probability of mutation,between 0 and 1 fmutation='simple'; % method of mutation % you can choose 'float';'simple'; lenchrom=[10 10 10 10 10]; % length of bit of every varible bound=[0 1;... 0 1;... 0 1;... 0 1;... 0 1]; 选择了二进制编码，tournament选择，均布交叉，单点变异。 注：采用二进制编码和grey编码时，交叉方法只能是simple，uniform，变异方法只能是simple lenchrom向量中表示变量表示成二进制的位数。 例三 maxgen=200; % maximum generation sizepop=100; % size of population AimFunc=StrAimFunc; % this is function of counting fitness fselect='roulette'; % method of select % you can choose 'tournament';'roulette' fcode='grey'; % method of coding % you can choose 'float';'grey';'binary' pcross=[0.6]; % probablity of crossover,between 0 and 1 fcross='uniform'; % method of crossover % you can choose 'float';'simple';'uniform' pmutation=[0.2]; % probability of mutation,between 0 and 1 fmutation='simple'; % method of mutation % you can choose 'float';'simple'; lenchrom=[10 10 10 10 10]; % length of bit of every varible bound=[0 1;... 0 1;... 0 1;... 0 1;... 0 1]; 选择了grey编码，roulette选择，均布交叉，单点变异。

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