Determination of master production schedule replanning frequency for various forecast window intervals

Determination of master production schedule replanning frequency for various forecast window... This paper examines the impact of forecast window intervals on replanning frequencies for a rolling horizon master production schedule (MPS). The problem environment for this study is an actual MPS operation of a paint company and includes features such as multiple production lines, multiple products, capacity constraints, minimum inventory requirements. A mixed integer goal programming model formulated for the MPS problem is used to analyze the impact of forecast window interval length on replanning frequencies and MPS performance in a rolling horizon setting. Given demand certainty, results indicate that the length of the forecast window interval influences the choice of replanning frequency for this company environment. A three‐month forecast window interval with a two‐month replanning frequency provided the best MPS performance in terms of total cost. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Operations & Production Management Emerald Publishing

Determination of master production schedule replanning frequency for various forecast window intervals

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Publisher
Emerald Publishing
Copyright
Copyright © 1998 MCB UP Ltd. All rights reserved.
ISSN
0144-3577
DOI
10.1108/01443579810217459
Publisher site
See Article on Publisher Site

Abstract

This paper examines the impact of forecast window intervals on replanning frequencies for a rolling horizon master production schedule (MPS). The problem environment for this study is an actual MPS operation of a paint company and includes features such as multiple production lines, multiple products, capacity constraints, minimum inventory requirements. A mixed integer goal programming model formulated for the MPS problem is used to analyze the impact of forecast window interval length on replanning frequencies and MPS performance in a rolling horizon setting. Given demand certainty, results indicate that the length of the forecast window interval influences the choice of replanning frequency for this company environment. A three‐month forecast window interval with a two‐month replanning frequency provided the best MPS performance in terms of total cost.

Journal

International Journal of Operations & Production ManagementEmerald Publishing

Published: Aug 1, 1998

Keywords: Forecasting; Models; Paint industry; Planning; Production scheduling

References

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