Right now the code doesn't run, can you clean up and show your complete code? It will be a lot easier to help you.

Right now the code doesn't run, can you clean up and show your complete code? It will be a lot easier to help you.

you must be using the classic gui (extension .mws), you want to use the standard gui (extension .mw).

I tested with V.13/Standard -- no problem.

you must be using the classic gui (extension .mws), you want to use the standard gui (extension .mw).

I tested with V.13/Standard -- no problem.

Lagrangean: Q[a]^(alpha) * Q[b]^(1-alpha) + lambda* (A-B*Q[a]-Q[b])

lambda: multiplier

first-order conditions:

alpha * Q[a]^(alpha-1) - lambda*B =0

(1-alpha)*Q[b]^(-alpha) - lambda = 0

simplifying, gives your FOC:

alpha * Q[a]^(alpha-1) = B * (1-alpha) * Q[b]^(-alpha)

yes it goes through (0,0). Now use the FOC and BC to solve for Q[a] and Q[b] in terms of A (unknown) and B, and alpha (known).

P.S. quickly done by hand, watch for typos -- your job is to automate that with Maple! All the best.

Lagrangean: Q[a]^(alpha) * Q[b]^(1-alpha) + lambda* (A-B*Q[a]-Q[b])

lambda: multiplier

first-order conditions:

alpha * Q[a]^(alpha-1) - lambda*B =0

(1-alpha)*Q[b]^(-alpha) - lambda = 0

simplifying, gives your FOC:

alpha * Q[a]^(alpha-1) = B * (1-alpha) * Q[b]^(-alpha)

yes it goes through (0,0). Now use the FOC and BC to solve for Q[a] and Q[b] in terms of A (unknown) and B, and alpha (known).

P.S. quickly done by hand, watch for typos -- your job is to automate that with Maple! All the best.

your first-order condition, if I recall correctly, will be a straight line through the origin -- it cuts your IC at the point you are looking for, and thence you can get the value of A such that the BC goes through that point too, i.e. once you've solved the problem the IC, BC, and FOC all go through the same point (the maximum of your constrained optimization problem).

your first-order condition, if I recall correctly, will be a straight line through the origin -- it cuts your IC at the point you are looking for, and thence you can get the value of A such that the BC goes through that point too, i.e. once you've solved the problem the IC, BC, and FOC all go through the same point (the maximum of your constrained optimization problem).

noted, thanks Robert.

noted, thanks Robert.

standard:

classic:

standard:

classic:

According to the Help menu,

The about(x1) function returns assumption and property information for x1. 
The getassumptions(x1) function returns the list of all relevant assumptions in the form expression::property. 

It sounds like these are very similar tasks, so one would expect about and getassumptions to return mutually consistent information, but:

about(P);
getassumptions(P);

-g:
  nothing known about this object


                  {g~::RealRange(Open(0), infinity)}

Probably a bug in about. If you say the last three words aloud, it sounds funny.

Wonderful job, I have already linked you:

http://www.mapleprimes.com/forum/whymapledoesnotsimplifywhatitshouldbe#comment-30685

I estimate that sum v. add comes up at least once a week.

Thanks pagan, I'll keep a record of these!