Research on Simulation-based Ordinal Optimization Methods with Applications to Production Scheduling of 300mm Foundry Fabs (2/3)
Date Issued
2005-07-31
Date
2005-07-31
Author(s)
DOI
932213E002043
Abstract
The three-year research objectives of this project are
(1) to design search space reduction methods for simulationbased
ordinal optimization (OO), (2) to develop these
methods into tool modules as part of an integrated system
optimization platform, and (3) to apply simulation-based OO
to effective production scheduling of 300mm foundry fabs.
In the first year, we considered the class of Stationary
Markov decision problems as the conveyer problem. We
proposed an idea of OO-Based Policy Iteration (OOBPI) to
handle the combinatorial complexity of decisions over the
time axis. Utilizing the framework of policy iteration, we
approximate the optimal cost-to-go and optimal decision of
each state by simulation-based OO. Preliminary numerical
studies indicated one order of speed-up of OOBPI over the
traditional simulation-based policy iteration.
In the second year, we have completed the design of
OOBPI algorithm, including the theories for the method,
convergence analysis, simulation study and exploration of
possible extension to general dynamic programming. In
developing a simulator of semiconductor wafer fabrication
with differentiated services, we have incorporated priority
service discipline into the simulator. We are now combining
OOBPI with the fab simulator to study dynamic composition
of production schedules for fabs.
Subjects
Ordinal Optimization
Policy Iteration
Algorithm design
Fab Simulator
Priority
Production
Scheduling
Scheduling
Publisher
臺北市：國立臺灣大學電機工程學系暨研究所
Type
report
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