With the sharp increase of uncertainty and complexity in production processes, dynamic scheduling nowadays plays a strong role in making enterprises more competitive: it is needed to handle real time events, such as machine breakdowns, job arrivals and stochastic processing times. The static job scheduling problem (JSP) is one of the most practically relevant but rather complex scheduling problems, having been proved to be NP hard, and it has been the subject of a significant amount of literature in the operations research field: however, this approach is unrealistic in real-world contexts, where dynamic events such as insertions, cancellations or modifications of orders, machine breakdowns, variation in due dates and processing times are inevitable and drive the realized execution of a static schedule far from its expected outcome and deteriorate the production efficiency seriously.