I have an absolute value objective function, minimizing the sum of abs( s[i] -
x[i] ) for two vectors s and x, with the constraints given by Ax = b where A is
a large but very sparse matrix.
So I'm using a dummy vector "u" in a MathProg model:
minimize least_abs_dev: sum {i in I} (u[i]);
s.t. constr1{i in I} : b[i] = sum{j in I} (A[i,j] * x[j]);
s.t. constr2{i in I} : u[i] >= (s[i] - x[i]);
s.t. constr3{i in I} : u[i] >= -(s[i] - x[i]);
I also eventually want to incorporate weights into the objective:
minimize least_abs_dev: sum {i in I} (u[i] * w[i]);
I've got this type of model working using MathProg and glpsol, but now I'm
trying to figure out how to translate it to the strict form required by the C
API. Has anyone done this? What's the best way to go about it? I'm going to
need high performance on some large problems.
I am fairly new to optimization and GLPK. Any help would be much appreciated.
- JM _______________________________________________
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