I'm struggling with one equation within a subtour elimination constraint.
$$\sum_{i \in S} \sum_{j \in S, j<i} y^t_{ij} \le \sum_{i \in S} z_{it} -z_{kt} \quad S \subseteq M \quad t \in T \quad \text{for some} \ k \in S$$
$$k=\textrm{argmax}_j\{z_{jt}\}$$
$$y^t_{ij} = z_{it} = \{0,1\} \quad \text{(binary decision variable)}$$
I'm not familiar with the term $\textrm{argmax}$. What's the exact meaning in this equation? What I've read is that an argument $z_{jt}$ must be found to maximize the function $f$. But there is no function, isn't it?
The whole equation is part of a MIP callback to add a lazy constraint (implemented with Gurobi solver).
I could be wrong, but I believe it can be read here simply as "the $j$ such that $z_{jt}$ is at its maximum value".