The objective of this research is to develop methodologies for sequencing and scheduling in uncertain manufacturing environments. The methodology involves an off-line optimization strategy, an on- line control scheme, and a "rescheduling" procedure. The off-line strategy utilizes a graph-theoretic formulation of the scheduling problem to generate a priori static schedules which take into account the presence of foreseeable system disruptions. A measure of schedule robustness will be developed for the off-line schedule. The on-line control structure is modeled as a discrete event dynamic system (DEDS). The research control structure incorporates the dynamic information about future disturbances to stabilize the operations schedule. The novelty of the approach is that it decomposes the overall control problem into non-myopic local problems which require minimum computation while retaining a global view of the system. The rescheduling procedure updates the static schedule after a major system disruption. The procedure generates an updated schedule which minimizes the scheduling delay and at the same time adheres closely to the off-line schedule. In contrast to the previous work on match-up scheduling, the research method has no need to determine the match-up time. The robustness and the applicability of the research methodology will be tested by experiments.
