I am new to the concept of robust optimization.I am trying to formulate the robust variation of a Binary Integer Program. Suppose we have a constraint of the form $\sum{x_{i,j}} \geq b_j$ for $ i \in I, j \in J$ with uncertainty in the rhs. We know that each value $b_j$ is going to deviate in a known interval and we known that a specific number of rhs's will deviate (e.g. $\Gamma$ uncertainty).

According to what I researched about the work of Bertsimas and Sim, they consider uncertainty only in the lhs or in the objective and they propose a method to reformulate the uncertainty from the rhs in the lhs by introducing a new variable. Is someone away how to do that or whether is any useful research papers that would help me reformulate the problem and come up with the Robust formulation?

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    $\begingroup$ This question: or.stackexchange.com/q/9882/51 seems quite similar. $\endgroup$
    – Rob
    Feb 17 at 13:55
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    $\begingroup$ It is similar but I have added additional clarification to what I am interested in $\endgroup$
    – Pia MiA
    Feb 17 at 16:43
  • $\begingroup$ Close votes were issued because this question was asking 2 questions rather than 1. I've removed the second question. $\endgroup$ Feb 19 at 22:02


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