Abstract
Real-life scheduling has to face many difficulties such as dynamics of manufacturing environments with unforeseen events occurring during the execution of a schedule. Namely, in the case of a resource failure, it may be necessary to process a lot of work again, or a feasible schedule recovery may not exist at all.
Moreover, the time window within which the ongoing schedule must be updated may be very short, and too time-consuming computation of the schedule may lead to a failure of the scheduling mechanism and setback in production. Our approach in the area of predictive-reactive scheduling is to allow for substitution of tasks, which cannot be executed, with a set of alternative tasks.
This paper makes use of the model of the hierarchical workflows and gives an SMT and a CSP models to recover an ongoing schedule from a resource failure with the objective to minimize the work processed in vain. The experimental analysis identified parameters for which the SMT model clearly outperforms the CSP model and vice versa.