ga in the command line
1 次查看(过去 30 天)
显示 更早的评论
k = 1:10;
fitnessfcn =@(x)( 2+2*k-exp(k*x(1))-exp(k*x(2)) );
x = ga(fitnessfcn, 2) % nvars=2; invoke an optimization routine
I am getting following errors;
Subscripted assignment dimension mismatch. Caused by: Failure in user-supplied fitness function evaluation. GA cannot continue.
Also how to add a Starting guess; x0 = [0.3 0.4]
thanking for kind help!
0 个评论
采纳的回答
Walter Roberson
2017-6-20
Your k is a vector, so ( 2+2*k-exp(k*x(1))-exp(k*x(2)) ) is a vector. However, your fitness function is required to return a scalar; https://www.mathworks.com/help/gads/ga.html#inputarg_fitnessfcn
There is no way to add a starting guess for ga. However, you can use an options structure that has InitialPopulationMatrix set in it. Scroll down a bit from https://www.mathworks.com/help/gads/ga.html#bs08mt8-4 to find the options description.
4 个评论
Walter Roberson
2017-6-20
编辑:Walter Roberson
2017-6-21
When you have a "for" loop that assigns to the same unindexed variable each time, and there are no randomization calls or other "side effects" being made, then the effect of the loop is the same as if you had only done the last iteration.
for k = 1:10;
fun =@(x) sum( 2 + 2*k-exp(k*x(1))-exp(k*x(2)) );
end
is the same as
k = 10;
fun =@(x) sum( 2 + 2*k-exp(k*x(1))-exp(k*x(2)) );
In turn, since k is going to be a scalar for that, and none of the sub-expressions create vectors, the result would be the same as
k = 10;
fun =@(x) 2 + 2*k-exp(k*x(1))-exp(k*x(2));
Also lsqnonlin minimizes the sum of squares of the values, whereas what you attempted to submit to ga would minimize the sum of the values, which is very different. The ga equivalent would be
k = 1 : 10;
fun =@(x) sum( (2 + 2*k-exp(k*x(1))-exp(k*x(2))).^2 );
更多回答(0 个)
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Genetic Algorithm 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!