I have the following problem formulated as a linear integer program:
\begin{align} & \text{minimize} && \sum_{i \in n} x_i\\ & \text{subject to} && \sum_{i \in n}{a_i}x_i \ge \theta_1, \\ & && \sum_{i \in n}{b_i}x_i \ge \theta_2, \\ & && a_i \ge 0 \quad \forall i \in n , \\ & && b_i \ge 0 \quad \forall i \in n , \\ & \text{and} && x_i \in \{0,1\} \quad \forall i \in n , \end{align} for any given $\sum_i a_i \geq \theta_1 \geq 0$ and $\sum_i b_i \geq \theta_2 \geq 0$
Another way of looking at it, is that we have a number of 2d tuples and we want to select the minimum number of tuples such that the sums over both dimensions are greater or equal to two thresholds. Does anyone know anything about the complexity of this problem? If we only have the first constraint: $ \sum_{i \in n}{a_i}x_i \ge \theta_1 $, and we drop the second: $\sum_{i \in n}{b_i}x_i \ge \theta_2$ (1D variant) then the problem is easy, we can just sort all $a_i$ in decreasing order, and pick the top ones until the threshold $\theta_1$ is satisfied. However, it seems to me that once we add the second constraint the problem becomes much harder (possibly NP-hard). Still, the idea of sorting and greedily picking elements gives at least a 2-approximation. Any clues?