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I have an MILP where we have $$ t_k = \sum_i P_i\cdot C_{ik} : P_i\ \in \{0,1\}, C_{ik} \in I^+ $$

and our model is constrained by the number of times $t_k$ is bigger than a certain value $T_k$.

$$ \left[\sum_k\left(t_k \ge T_k\right)\right] \ge N $$

where $N$ is the minimum number of constraints to be satisfied.

Can this problem be solved in MILP and how? I am new to this domain and any leads would be very helpful.

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  • $\begingroup$ Are $P_i$ and $C_{ik}$ both variables? $\endgroup$
    – prubin
    Mar 22 at 20:37
  • $\begingroup$ $P_i$ is a binary variable. $C_{ik}$ is a positive constant. $\endgroup$ Mar 23 at 5:59
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You can introduce a binary variable $x_k$ and linear constraints \begin{align} \sum_k x_k &\ge N\tag1\\ -t_k+T_k&\le M_k(1-x_k) &&\text{for $k\in K$}\tag2 \end{align} Here, the “big-M” constant $M_k$ is a small upper bound on $-t_k+T_k$. Because $t_k\ge 0$, you can take $M_k=T_k$, and the constraint simplifies to $t_k\ge T_k x_k$.

Constraint $(1)$ forces at least $N$ of the $x_k$ variables to be $1$. Constraint $(2)$ enforces the logical implication $x_k=1\implies t_k\ge T_k$.

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  • $\begingroup$ I want to edit k index in my question. But without making your answer seems out of place. Thank you for your help. $\endgroup$ Mar 23 at 6:45
  • $\begingroup$ I updated both question and answer just now. $\endgroup$
    – RobPratt
    Mar 23 at 12:49

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