GAMS World Forum

cladelpino

This is the kind of approach that I am thinking of when I say that to prove if a solution is feasible or not is "easy". It is as hard as writing the fixing of the variables for each variable block you have (and you don't seem to have many blocks, rather many elements within a block) set ma...

cladelpino

In the NLP context, the "path" that the solver follows is non-trivial and faced with many challenges. All that you are observing is "normal" behaviour for this type of problems. For the specific case of division, your approach: I managed to multiply through by x and get rid of th...

cladelpino

I honestly don't know. Looking around also I couldn't find a clear reference for the errors.

On the other hand, it is "easy" to see if a given solution is infeasible. Why don't you figure that out so that you're sure ?

Best and good luck
Claudio

cladelpino

If there are two solve statements in the same file, in the second one every shared variable will have its value (.l attribute) set by the first solve.

cladelpino

It depends on if the problem is convex or non-convex. If the problem is convex, (considering a well-scaled, well-bounded model), using the "crossover" stop criterion should yield the global optimum. But, if the problem is non-convex this criterion can stop prematurely. If this is the case,...

cladelpino

In the manual it is said that I have to use the ".L variable attribute"

Following this path, you can:

Code: Select all

parameter xInitial(t,household);
binary variable x(t,household);

*I assume there is a proper $gdxin somewhere
$load xInitial

x.L(t,household) = xInitial(t,household);

cladelpino

Matrix product between matrix A and vector x: set i /i1*i3/ set j /j1*j4/ parameter A(i,j),x(j),matProd(i); *You can set some values for A and x if you want to test the code *Here I just set it to random integers drawn from an uniform distribution A(i,j)=uniformint(0,10); x(j)=uniformint(0,10); matP...

cladelpino

https://www.gams.com/latest/docs/UG_Dat ... Excel.html

cladelpino

Just to add small data, COUENNE also reports 18.00 as the optimal solution, so BARON is not agreeing here. Furthermore, if you feed the solution back to BARON it is correctly identified as optimal.

PS: Are you aware that a MILP formulation can (I think) also be written for PSP-2 ?

cladelpino

Not familiar with SAA. The code does what it says. Can you be more specific as to what is the behaviour that you don't desire ? My problem is that as the model runs the problem, it changes the first set of binary variables, i.e., x, to positive variables. which Model (Finall,Finalls, etc) ? all of t...

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