Robust optimization: Difference between revisions

Revision as of 16:40, 21 June 2007

Revision as of 23:47, 10 October 2007

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:<math>\min cx + dy: Ax=b, Bx + Cy = e, x, y \le 0,</math>

where d, B, C and e are random variables with possible realizations <math>{(d(s), B(s), C(s), e(s): s \in \{1,...,N\})}</math>, where (N = the number of scenarios). The robust optimization model for this LP is:

:<math>\min f(x, y(1), ..., y(N)) + wP(z(1), ..., z(N)): Ax=b, x \le 0,</math>