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Hi all,

First of all, I would like to mention that I'm new to Maple, so please excuse my lack of knowledge.

I have a rather complicated expression, let us call it expr, and I have a constraint equation, let us call it constr = 0. I would like to simplify expr knowing that constr = 0.

Stupid example:

expr: 2*x+4*y+3

constr: x+2*y = 0

In that case:

expr = 2*(x+2*y)+3 = 2*0+3 = 3

How can I do that?

Thanks a lot.

Hello, I'm creating a rolling thin disk (rolling without slip) in the MapleSim, the model like the picture below (Fig. 1).

       ...

Hi people!

Why there is not a "Modelica.Mechanics.MultiBody.Joints.RollingWheel" (different from 1-D mechanics rolling wheel) in MapleSim 5? It is previewed in the Modelica language and SystemModeler has this implementation.

Is there a way to import the model o this joint from somewhere? If not, how could I model this non-holonimic constraint in MapleSim? 

Thanks! 

I have a non linear Sharpe ratio with 3 portfolio weights w1,w2 and w2. I want to (globally) maximize the sharpe ratio by choosing w1,w2 and w2 subject to the constraints that each of the variables is in the range of 0 to 1, and that their summation is equal to 1. I also want the maximization to start at an initial point of [w1=0.35,w2=0.6,w3=0.05].

The function is:

SR:= (0.012w1+0.007w2+0.0384w3-0.009)/(stdev)

where stdev is the standard deviation of the portfolio ...

I'm having trouble maximizing this funciton:

S=  (w1*E1+w2*E2+w3*E3)/(CoVar[1,2]), subject to the constraint w1+w2+w3=1

I need it to choose w1, w2, and w3 to maximize S

Does anybody know how to configure the model to obtain the position constraint equations of a slider-crank mechanism as:

l1·cos(theta)+l2·sin(beta)-s = 0
l1·sin(theta)-l2·cos(beta) = 0

instead as obtained in the help-example on:
http://www.maplesoft.com/support/help/MapleSim/view.aspx?path=MapleSim/Multibody/Kinematic_Exports

Thanks in advance

Ok, when I run the below code which maximize the risk adjuested portfolio returns
(long and short positions) in QP matrix form on empirical data I get very strange
allocations ie we go 100% or 100% short in almost all stocks except for a few
where the allocations are more appropriate like 0.2 etc.


# Maximize Risk Adjuested Return Matrix Form
# Minimize W'.Cov.W−W'.EV
# R=Return Matrix

EV := Vector([seq(ExpectedValue(Column(R, i)), i = 1 .. N)], datatype = float[8]):