An Exploratory Analysis of Two Iterative Linear Programming-Simulation Approaches for Production Planning

Production planning models that aim at determining optimal release schedules for production facilities face a fundamental circularity. In order to match supply to demand in an optimal manner, they must recognize the cycle time that elapses between material being released into the plant and its emerg...

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Bibliographic Details
Published in:IEEE transactions on semiconductor manufacturing 2010-08, Vol.23 (3), p.442-455
Main Authors: Irdem, D Fatih, Kacar, Necip Baris, Uzsoy, Reha
Format: Article
Language:English
Subjects:
Algorithms
Applied sciences
Circularity
Computational modeling
Convergence
Cycle time
Electronics
Emergence
Exact sciences and technology
Flow times
Iterative methods
Linear programming
linear programming (LP)
Mathematical models
Microelectronic fabrication (materials and surfaces technology)
Operations research
Optimization
Processor scheduling
Production facilities
Production planning
Resource management
Schedules
Scheduling algorithm
Semiconductor electronics. Microelectronics. Optoelectronics. Solid state devices
Semiconductors
simulation
Studies
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Summary:Production planning models that aim at determining optimal release schedules for production facilities face a fundamental circularity. In order to match supply to demand in an optimal manner, they must recognize the cycle time that elapses between material being released into the plant and its emergence as finished product. However, it is well known from queuing models that the mean cycle time increases nonlinearly with resource utilization, which is determined by the release schedule. To address this circularity, a number of authors have suggested algorithms which iterate between a linear programming model that determines releases for a set of flow time estimates, and a simulation model that evaluates the production realized from that release schedule. We present computational experiments examining the behavior of two such algorithms. We find that the convergence behavior of one is significantly more consistent than that of the other, and explore insights that may lead to improved algorithms.
ISSN:0894-6507
1558-2345
DOI:10.1109/TSM.2010.2051751