There is a model Q(t)= a1*A(t)+ a2*B(t)+ a3*A(t)^2*B(t)+ a4*A(t)*B(t) ^2+a5* B(t) ^3+ a6 A(t) ^3+ a7*A(t) ^2*C(t)
Where P(t), A(t), B(t) and C(t) are known for any point of time or a sample of time.
Then I want to obtain the value of a1, a2, a3,a4,a5,a6,a7 with constrained a1>0, a20,a4>0, a6>0, a5 and a7 unbounded
So that P(t)-Q(t) become minimum or negligible at any point of time.
Seems like you can use the simplex algorithm to solve this:
http://en.wikipedia.org/wiki/Simplex_algorithm
But I'm not sure since it's been a while since I last worked in "Operation Research" where these kind of problems are common. In any case you might also want to check some libraries to help you. Check this Python function:
http://docs.scipy.org/doc/scipy/reference/tutorial/optimize.html
You have tagged this copy with "C" language and you can search Scipy library for the C code for it (think of Python as high-level C/C++) since the base code is almost always made with C or C++.
Best of luck.
Seems like you can use the simplex algorithm to solve this:
http://en.wikipedia.org/wiki/Simplex_algorithm
But I'm not sure since it's been a while since I last worked in "Operation Research" where these kind of problems are common. In any case you might also want to check some libraries to help you. Check this Python function:
http://docs.scipy.org/doc/scipy/reference/tutorial/optimize.html
You have tagged this copy with "C" language and you can search Scipy library for the C code for it (think of Python as high-level C/C++) since the base code is almost always made with C or C++.
Best of luck.
MLAB will fit this model with your constraints. Goto www.civilized.com
and download a copy and try it.
this scipy might be useul: http://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html
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