Matlab中遗传算法的优化 [英] Optimization with genetic algorithm in matlab

问题描述

我已经使用遗传算法编写了一个简单的优化代码.我不知道为什么在运行代码时会出错.这是我的代码:

I have written a simple optimization code using genetic algorithm.I don't know why I get error during running the code.Here is my code:

f = @(x1,x2) 1-x1.^2+(x1-x2).^2;

A = [1 1;-1 2;2 1];
b =[2 2 3]' ;
Aeq = [];
beq = [];
Lb = [0 0]';
Ub = [];

[Xopt,Fval] = ga(f,2,A,b,Aeq,beq,Lb,Ub)

我不知道为什么matlab会给我错误.我根据遗传算法文档"(Genetic algorithm Documentation)编写了该程序.一点仍然给我错误:

I don not know why matlab gives me error.I wrote this programm based on the "Genetic algorithm Documentation" bit still gives me error:

Error using @(x1,x2)1-x1.^2+(x1-x2).^2
Not enough input arguments.
Error in createAnonymousFcn>@(x)fcn(x,FcnArgs{:}) (line 11)
fcn_handle = @(x) fcn(x,FcnArgs{:});

Error in makeState (line 48)
            firstMemberScore = FitnessFcn(state.Population(initScoreProvided+1,:));

Error in galincon (line 18)
state = makeState(GenomeLength,FitnessFcn,Iterate,output.problemtype,options);

Error in ga (line 351)
            [x,fval,exitFlag,output,population,scores] = galincon(FitnessFcn,nvars, ...

Caused by:
    Failure in initial user-supplied fitness function evaluation. GA cannot continue

推荐答案

MATLAB中所有优化方法的目标函数仅接受1个参数.根据 ga文档:

Objective functions of all optimization methods in MATLAB only accept 1 argument. According to ga documents:

乐趣-目标功能

客观函数，指定为函数句柄或函数名称.写目标函数接受长度为 nvars 的行向量并返回标量值.

Objective function, specified as a function handle or function name. Write the objective function to accept a row vector of length nvars and return a scalar value.

当"UseVectorized"选项为true时，请写有趣的文字来接受pop-by-nvars矩阵，其中pop是当前人口规模.在这个在这种情况下，fun返回一个与pop长度相同的向量，其中包含适应度函数值.确保乐趣不会带来任何后果流行音乐的特定大小，因为ga可以传递a的单个成员人口，甚至在向量化的计算中.

When the 'UseVectorized' option is true, write fun to accept a pop-by-nvars matrix, where pop is the current population size. In this case, fun returns a vector the same length as pop containing the fitness function values. Ensure that fun does not assume any particular size for pop, since ga can pass a single member of a population even in a vectorized calculation.

更改目标函数，它应该起作用:

Change you objective function and it should work:

f = @(x) 1-x(1).^2+(x(1)-x(2)).^2;

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