New jobs arrival, jobs cancelation or machine breakdowns, are unexpected events that may occur during production run in real environments, thus disrupting the established schedule. Hence, rescheduling process is necessary for efficiently revising the initial schedule, preferably with little movements. In the literature, many scheduling problems consider unlimited buffer spaces between successive machines in flow shop environments. However, in real life systems, the capacity between machines may be limited or no-store existing. To fill the void, this paper considers a flow shop rescheduling problem with mixed blocking constraints, under disruptions caused by new jobs arrival. A new performance measure is investigated, considering simultaneously the schedule efficiency measured by the total weighted waiting time, and the schedule stability evaluated by the total weighted completion time deviation. This combination could be very helpful for real life industrial systems. A mixed integer linear programming model (MILP) is designed, as well as an iterative methodology based on the predictive reactive rescheduling strategy. At last, two heuristic methods are implemented and discussed, in terms of solution quality and computing time