Does it make sense to scale bounds for 'lsqnonlin'?
2 次查看(过去 30 天)
显示 更早的评论
Hello,
I am wondering if I need to scale the initial guess vector as well as lower and upper bounds when dealing with MATLAB optimizers ("lsqnonlin" is of special interest). In other words, do the bounds have to be normalized, say, in the range [0 1]? Some of the unknown parameters in my optimization problem are several orders higher than the others so I do pre- and postmultiply them by certain numbers so that the ranges for all of the parameters are approximately equal. However, I would like to figure out if that is necessary at all. Does the "lsqnonlin" have a built-in scaling?
Thank you, Igor.
0 个评论
回答(1 个)
Wu Wen
2017-4-7
Hi,
I'm doing something similar. I don't know exactly how the function 'lsqnonlin' works, but I'm gonna do some parametric study to investigate the sensitivity of the optimization to the scaling of the variables . I'm trying to make them close to the output value of the objective function. Please can you tell me if you solved this problem? Thank you.
2 个评论
Wu Wen
2017-4-12
Hello,
I've done a series of optimizations with different scaling coefficients and I've got very different results. Basically you can control the size of the iteration step of the optimization process by using different scaling factors. If the steps are too small then the optimization does not progress much.
另请参阅
类别
在 Help Center 和 File Exchange 中查找有关 Get Started with Optimization Toolbox 的更多信息
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!