Using Robust Optimization for Diet Problem

Hi @Kostas Vasilakakis. Could you share your AIMMS project including the changes you made to include robust optimization? Please include the entire AIMMS project folder in a ZIP file, and attach the ZIP file here.

Your model contains several errors:

First, in the objective you use a construct like x(d)/p where p is an uncertain parameter. Uncertain parameters cannot be used in a “nonlinear” operator so you cannot use 1/p. One way of resolving this is by introducing a new variable y(d) and change the definition of variable x(d) into y(d) * p. And use y(d) instead of x(d)/p in the definition of the objective.

Second, in the constraint ‘AchieveDailyPerPersonFoodCostInFandB’ you have an equality constraint of the form x + y + z  = p with p an uncertain parameter. This constraint is infeasible as it cannot be satisfied for different values of p; for example the system x + y + z = 1 and x + y + z = 2 has no feasible solution. Only if you change the variables in this constraint into adjustable variables depending on p (see the Language Reference) this is a feasible construction. But in your model you do not use adjustable variables.

Third, in your model you use binary variables but you defined the math program type as LP. This should be MIP (or Automatic).