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problem := ur+dr, {con1, con4, con5}, seq(w[i] = 0 .. 1, i = 1 .. N):
problem_matrix_form := Optimization:-Convert:-AlgebraicForm:-LPToMatrix(problem):

Optimization:-LPSolve(problem, maximize = true);
Optimization:-LPSolve(problem_matrix_form[2 .. 4], maximize = true);


The above trick-conversion method works for all LP and QP problems
However it does not work on NLP problems. I have attached the workshet

Hello everyone. I am new to Maple. I am trying to simplify an expression in Maple. The expression is like:

u := a+b*x+a/x+b*x^7+c

If I use simplify(u) Maple returns the result as:

 (a*x+b*x^2+a+b*x^8+c*x)/x

If I want the result in the form:

u = a*(x+1)/x+b*x*(1+x^6)+c

or

u = a*(1+1/x)+b*x*(1+x^6)+c

How should I proceed? Is it possible to do this?

Ok, first of all I renamed the return matrix R (A is allready used)
I now think I got two of them (minimize portfolio variance and minimize portfolio variance for a
given expected return in matrix form) figured out:


Cov := Matrix(CovarianceMatrix(R), datatype = float):
pr := .6*max([seq(ExpectedValue(Column(R, i)), i = 1 .. nstock)]):

A := Matrix([[seq(1, i = 1 .. nstock)]], datatype = float):
b := Vector([1], datatype = float):
Aeq := Matrix(...