Hi, I am running proc optmodel using MILP solver on two different datasets (let's call them A & B) but more or less equivalent in terms of #variables, #integers, #constraints etc. Surprisingly, A takes 16 min to converge, while B converges in negligible time (2-3 seconds). However, B seems to give correct output (I am also running Excel Analytic Solver Platform for the same problem, and results more or less match with that of SAS/OR). The code for A & B are exactly same. Any help will be greatly appreciated. ... View more

Is Minimize ∑[x(i)+y(i)] the exact equivalent of ∑x(i)+∑y(i) for a LPP? Some time back, I read somewhere that the formulation ∑x(i)+∑y(i) is more effective than ∑[x(i)+y(i)] because we are minimizing each section of the objective function separately. Same for maximizaton. Is this correct? Can it be mathematically proved if this is correct or incorrect? ... View more

I have a constraint which sums the nonzero elements of a sparse matrix. To do this, I am using the SLICE expression, so my constraint reads like this: con test{t in ASC}:sum{u in slice(<t,*>,Map)}y>=0; Here 'Map' is a sparse matrix, with 2 mapped variables - ASC and UIN, i.e. 'Map' contains all eligible pairs of ASC and UIN. The constraint should work like this: For each element 't' of ASC, it should check whether 't' has a corresponding value 'u' for UIN variable. If there is, then it adds y for that row. However, when I run this constraint, I get a "Constraint is empty" error. What am I doing wrong here/is there a better way of doing this? ... View more

I have a parameter 'slope' which depends on 3 parameters (Sets): physician, product and linear_piece I want to read this data in proc optmodel using 'Read data into...' My code is something like this: read data Slope1         into Slope1 = [Physician Product Linear_piece] Slope   Slope[Physician, Product, Linear_piece] = col("Slope"); However this doesn't seem to be working. Is there anything wrong with the code? ... View more

Hi, I have a binary variable x(b) where b ranges from 1 to 5. Now I have a constraint which says that summation of x(b) over all b is either 0 or 3. However all the x(b)'s with value 1 need to be together. For example I can have the following sequences: 0 0 0 0 0 0 0 1 1 1 0 1 1 1 0 1 1 1 0 0 However I cannot have the following sequences. 1 0 1 0 1 0 1 1 0 1 Any help in formulating this constraint will be greatly appreciated. ... View more