We consider the Advanced Scheduling Problem (ASP) assuming a block scheduling strategy. A set of patients and the related surgery waiting list are given, together with a set of Operating Room (OR) blocks and a planning horizon. The problem asks to determine the subset of patients to be scheduled and their assignment to the available OR blocks. We consider a so-called rolling horizon approach in order to solve the ASP over a planning horizon of several weeks. The approach is iterative and readjusts the schedule each week: at each iteration the mid-term schedule over the next $n$ weeks is generated by solving an optimization problem, minimizing a penalty function based on patients' delay and tardiness; the first week schedule is then implemented. Unpredictable extensions of surgeries and new arrivals may disrupt the schedule. The schedule is then repaired in the next week iteration, again optimizing over $n$ weeks the penalty function while limiting the number of disruptions from the previously computed plan. The total delay and tardiness minimization problem is formulated as an ILP model and solved with a commercial solver. A deterministic formulation and a robust one are proposed and compared over different stochastic realization of surgery times.
