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A multi-product lot size in make-to-order supply chain using discrete event simulation and response surface methodology

A multi-product lot size in make-to-order supply chain using discrete event simulation and... This paper develops a simulation optimisation approach for solving the Lot-Sizing Problem (LSP) in Make-to-Order (MTO) supply chain. For this purpose, a discrete event simulation model was firstly implemented as a tool in estimating Order Mean Flow Time (OMFT) performance. Secondly, a multiple-objective optimisation was achieved by applying Response Surface Methodology (RSM). A comprehensive case study is detailed which involves a multi-product, multi-stage, multi-location production planning with capacity-constrained and stochastic parameters such as lot arrivals order, transit time, set-up time, processing time, etc. The objective of the proposed approach is to determine the fixed optimal lot size for each manufacturing product type that will ensure OMFT target value for each finished product type. The study results illustrate that the LSP in MTO sector is viable and provide a prototype for further research on simulation optimisation approaches. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Services, Economics and Management Inderscience Publishers

A multi-product lot size in make-to-order supply chain using discrete event simulation and response surface methodology

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Publisher
Inderscience Publishers
Copyright
Copyright © Inderscience Enterprises Ltd. All rights reserved
ISSN
1753-0822
eISSN
1753-0830
DOI
10.1504/IJSEM.2010.033366
Publisher site
See Article on Publisher Site

Abstract

This paper develops a simulation optimisation approach for solving the Lot-Sizing Problem (LSP) in Make-to-Order (MTO) supply chain. For this purpose, a discrete event simulation model was firstly implemented as a tool in estimating Order Mean Flow Time (OMFT) performance. Secondly, a multiple-objective optimisation was achieved by applying Response Surface Methodology (RSM). A comprehensive case study is detailed which involves a multi-product, multi-stage, multi-location production planning with capacity-constrained and stochastic parameters such as lot arrivals order, transit time, set-up time, processing time, etc. The objective of the proposed approach is to determine the fixed optimal lot size for each manufacturing product type that will ensure OMFT target value for each finished product type. The study results illustrate that the LSP in MTO sector is viable and provide a prototype for further research on simulation optimisation approaches.

Journal

International Journal of Services, Economics and ManagementInderscience Publishers

Published: Jan 1, 2010

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