Originally posted by: D_Culver

I'm having trouble modeling the L-2 Norm of a sum of decision variables in my objective function. I was unable to find an OPL function that does this and I have tried unsuccessfully a number of methods to simply take the square root of the squares of the variables. Does anyone have any ideas on how I can go about doing this? Thanks.
#DecisionOptimization
#OPLusingCPLEXOptimizer

Originally posted by: D_Culver

Below is my objective function and corresponding constraint. When I run this I receive the error message that Q is not positive semi-definite. What am I doing wrong?

dvar float+ q;
dvar boolean yi in MISSIONSc in CONFIGSt in TIME;

maximize Pi * q;

st.

sum(i in MISSIONS, c in CONFIGS)(ObsVal_Range[i][c]*sum(t in TIME)y[i][c][t])^2 >= q^2;

Both Pi and ObsVal_Range[i][c] are model parameters.
#DecisionOptimization
#OPLusingCPLEXOptimizer