Estimating Clearing Functions for Production Resources Using Simulation Optimization
We implement a gradient-based simulation optimization approach, the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm, to estimate clearing functions (CFs) that describe the expected output of a production resource as a function of its expected workload from empirical data. Instead...
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| Vydáno v: | IEEE transactions on automation science and engineering Ročník 12; číslo 2; s. 539 - 552 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
New York
IEEE
01.04.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Témata: | |
| ISSN: | 1545-5955, 1558-3783 |
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| Abstract | We implement a gradient-based simulation optimization approach, the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm, to estimate clearing functions (CFs) that describe the expected output of a production resource as a function of its expected workload from empirical data. Instead of trying to optimize the fit of the CF to the data, we seek values of the CF parameters that optimize the expected performance for the system when the fitted CFs are used to develop release schedules. A simulation model of a scaled-down wafer fabrication facility is used to generate the data and evaluate the performance of the CFs obtained from the SPSA. We show that SPSA significantly improves the production plan by either searching for better CF parameters or by directly optimizing releases. |
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| AbstractList | We implement a gradient-based simulation optimization approach, the Simultaneous Perturbation Stochastic Approximation (SPSA) algorithm, to estimate clearing functions (CFs) that describe the expected output of a production resource as a function of its expected workload from empirical data. Instead of trying to optimize the fit of the CF to the data, we seek values of the CF parameters that optimize the expected performance for the system when the fitted CFs are used to develop release schedules. A simulation model of a scaled-down wafer fabrication facility is used to generate the data and evaluate the performance of the CFs obtained from the SPSA. We show that SPSA significantly improves the production plan by either searching for better CF parameters or by directly optimizing releases. |
| Author | Uzsoy, Reha Kacar, Necip Baris |
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| References_xml | – volume: 40 start-page: 206 year: 2007 ident: ref31 article-title: Work in process clearing in supply chain operations planning publication-title: IIE Trans doi: 10.1080/07408170701487997 – start-page: 51 year: 1997 ident: ref37 article-title: Focusing maintenance improvement efforts in a wafer fabrication facility operating under theory of constraints publication-title: Prod Inventory Manage – ident: ref34 doi: 10.1016/j.ijpe.2011.09.012 – ident: ref27 doi: 10.1109/TSM.2010.2051751 – ident: ref30 doi: 10.1016/j.ijpe.2008.11.014 – ident: ref19 doi: 10.1287/mnsc.29.10.1126 – year: 1980 ident: ref41 publication-title: Practical Nonparametric Statistics – ident: ref23 doi: 10.1109/66.492820 – ident: ref26 doi: 10.1109/WSC.2008.4736317 – ident: ref22 doi: 10.1016/j.ejor.2004.01.019 – ident: ref2 doi: 10.1287/mnsc.2.2.159 – ident: ref38 doi: 10.1287/ijoc.14.3.192.113 – year: 2012 ident: ref36 publication-title: Fitting clearing functions to empirical data simulation optimization and heuristic algorithms – ident: ref29 doi: 10.1016/0925-5273(93)90085-Y – ident: ref28 doi: 10.1287/mnsc.37.8.1015 – volume: 73 start-page: 165 year: 2001 ident: ref24 article-title: Extended model for a hybrid production planning approach publication-title: Int J Prod Econ doi: 10.1016/S0925-5273(00)00172-9 – ident: ref16 doi: 10.1007/978-3-540-24764-7 – ident: ref6 doi: 10.1287/opre.34.4.522 – start-page: 437 year: 2010 ident: ref14 publication-title: Planning Production and Inventories in the Extended Enterprise A State of the Art Handbook – ident: ref17 doi: 10.1016/j.ijpe.2005.09.001 – ident: ref10 doi: 10.1109/TSM.2005.863214 – volume: 1 start-page: 593 year: 2010 ident: ref39 publication-title: Planning Production and Inventories in the Extemnded Enterprise A State of the Art Handbook – year: 1960 ident: ref3 publication-title: Planning Production Inventories and Work Force – year: 0 ident: ref33 article-title: An exploratory study of disaggregated clearing functions for multiple product single machine production environments publication-title: Int J Prod Res – ident: ref25 doi: 10.1109/TASE.2009.2021462 – year: 1993 ident: ref4 publication-title: Stochastic Models of Manufacturing Systems – ident: ref15 doi: 10.1080/00207548208947752 – ident: ref11 doi: 10.1109/TSM.2011.2176560 – year: 2011 ident: ref32 article-title: Empirical validation of meta-models of work centers in order release planning publication-title: Workshop Prod Econ – year: 2001 ident: ref5 publication-title: Factory Physics Foundations of Manufacturing Management – year: 1988 ident: ref8 article-title: Resource pricing and aggregate scheduling in manufacturing systems publication-title: Graduate School of Ind Admin Carnegie-Mellon Univ – ident: ref9 doi: 10.1002/nav.20335 – year: 2006 ident: ref21 publication-title: Production Planning by Mixed Integer Programming – ident: ref20 doi: 10.1287/mnsc.35.4.478 – year: 2000 ident: ref18 publication-title: Foundations of Inventory Management – volume: 2 year: 1989 ident: ref7 article-title: Capacity loading and release planning with work-in-progress (WIP) and lead-times publication-title: J Manuf Oper Manage – year: 1974 ident: ref13 publication-title: Operations Research in Production Planning Scheduling and Inventory Control – ident: ref12 doi: 10.1080/00207540110090939 – ident: ref1 doi: 10.2307/1905580 – ident: ref40 doi: 10.1109/7.705889 – ident: ref35 doi: 10.1109/WSC.2010.5678899 |
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| SubjectTerms | Automation Clearing function Data models linear programming Optimization Optimization algorithms Planning Production planning Production systems Simulation simulation optimization Stochastic models workload-dependent lead times |
| Title | Estimating Clearing Functions for Production Resources Using Simulation Optimization |
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