Job Shop Scheduling Problem has been widely researched from a static and deterministic perspective. This research aims to study the complexity and imminent uncertainty of real-life production environments from a dynamic and stochastic approach, based on a rescheduling model in response to interruptions in the production system related to the arrival of new jobs, cancellation of work orders, lack of material and/or personnel, machine failures, job priority changes and stochastic processing times, among others. A predictive-reactive rescheduling strategy and a hybrid rescheduling policy are proposed. A genetic algorithm is used with the objective of minimizing multiple objectives.