CAREER: Scheduling of Multiclass Queueing Networks via Fluid Models

University Of Texas At Austin, Austin TX

Investigators

Abstract

Due to the advent of highly complex manufacturing, communication, and computer systems, there has been an increased need for more complex and realistic mathematical models to analyze and control such systems. A particularly striking example is seen in semiconductor wafer fabrication, where one facility may manufacture multiple products which traverse a labyrinthine route consisting of hundreds of steps. Factors such as reentrant routing, varied processing speeds, setup times, and machine downtimes make such systems particularly difficult to evaluate and control. Fluid models in queueing can be thought of as a relaxation of an original multiclass queuing network which can provide crucial insight into the operation of complex reentrant systems. The proposed research plan involves exploring fluid model techniques for efficient scheduling of multiclass queuing models. First we propose developing robust and efficient algorithms for solving a fluid model control problem. Then we will develop techniques for translating the solution to the fluid control problem into a feasible near-optimal schedule for the original. Finally, we will test the applicability of our methods using realistic wafer fab data of practical size and scope, drawing on a partnership with International SEMATECH for fab data and benchmark simulation models. The proposed education plan is tied in with the research plan and involves new course development and software development for undergraduate courses and graduate courses in operations research modeling and queueing theory.