9522795 Van Oyen This research focuses on scheduling and release/admission control in systems for which the production process entails heterogeneous job types, service times, service delay penalties, and due dates as well as significant random variability in any or all of the following aspects: arrival process, job service times, and set-up overhead. In addition, the research develops models and methods of analysis for system control subject to incomplete observations of system state information. To achieve this, the research focuses on the development of an integrated analysis and design methodology to perform dynamic resource allocation for an extended class of polling models to address dynamic (state-dependent) control for queuing systems with incomplete state observations, set-up times/costs, and target production levels. The approach incorporates three core elements: (1) the characterization of optimal dynamic policies, (2) the computation of approximately optimal policies, and (3) the summary of insights gained from theoretical and numerical investigations in a set of operating principles for a class of problem instances. This research will culminate in the development of a methodology for the analysis and design of dynamia control algorithms for the control of queuing systems with incomplete state observations. Advanced scheduling and production control algorithms promise to yield significant performance advantages to manufacturing operations that employ them, provided they are built upon deeply rooted concepts. This research addresses a class of control problems in queuing networks that center on scheduling policies (and their interaction with release policies) for systems with significant switching (set-up) times and incomplete observation of the system state. The results from this research will impact a class of problems in resource allocation directly relevant to a broad range of manufacturing facilities. Moreover, the models, methods, and control algorithms developed will be u seful in emerging information networks and systems, which contain similar optimization issues.
