A COMPARISON OF PRODUCTION SCHEDULING POLICIES ON COSTS, SERVICE LEVEL, AND SCHEDULE CHANGES

Authors

  • Richard Metters,

    1. Cox School of Business, Southern Methodist University, Dallas, Texas 15275–0333, USA
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      Vicente Vargasi s AssistantP rofessoor f Decisiona nd InformationA nalysis at the Goizueta Business School, Emory University. He holdsa Ph.D. from the Kenan-Flagle Brusines School, University of North Carolina. His current research interests in cludet he application of Data Envelopment Analysis (DEA) in multicriteria optimization, yield managemenmt, aster production schedulein stability in make-to-stock and assemble-to-order production environments and mixed model assembly scheduling under JIT production. He has published in IJE Transactions and International Journal of Production Research.

  • Vicente Vargas

    1. Goizueta Business School, Emory University, Atlanta, Georgia 30322–2710, USA
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      Richard Metters is Assistant Professor at the Cox School of Business Southern Methodist University. He holds a Ph.D. from the Kenan-Flagler Business School, University of North Carolina, an MBA from Duke University anda B.A. from Stanford University. His research interests concentrate in both manufacturing and service sector applications of stochastic inventory theory. He has previously published in IIE Transactions, Journal of Operations Management, International Journal of Production Research, European Journal of Operational Research, Journal of the Operational Research Society, and Production and Inventory Management Journal.


Abstract

We consider a single product, single level, stochastic master production scheduling (Mps) model where decisions are made under rolling planning horizons. Outcomes of interest are cost, service level, and schedule stability. The subject of this research is the Mps control system: the method used in determining the amount of stock planned for production in each time period. Typically, Mps control systems utilize a single buffer stock. Here, two Mps dual-buffer stock systems are developed and tested by simulation. We extend the data envelopment analysis (dea) methodology to aid in the evaluation of the simulation results, where Dea serves to increase the scope of the experimental design. Results indicate that the dual-buffer control systems outperform existing policies.

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