Louis Duhem, Maha Ben Ali, Michael Morin and Jonathan Gaudreault
Paper (2024)
An external link is available for this itemAbstract
In today's dynamic markets, decision-making relies heavily on simulation models to evaluate different production control methods. Although price-driven production control methods have proven their effectiveness in exploiting price volatility, certain industries are still reluctant to adopt these methods in their operational decision-making. This research demonstrates the relevance of price-driven methods for the wood products industry. A sawmill simulator is used to illustrate this. Since the simulation of the sawmill production process is time-consuming, we propose a probabilistic sampling-based method to rationalize the dataset size. A comparative study shows that exploiting historical and recent price data increases sawmill revenues.
Uncontrolled Keywords
industries; planing; decision making; production control; machine learning; probabilistic logic; delays
Subjects: |
1600 Industrial engineering > 1600 Industrial engineering 1600 Industrial engineering > 1606 Operations management |
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Department: | Department of Mathematics and Industrial Engineering |
PolyPublie URL: | https://publications.polymtl.ca/59311/ |
Conference Title: | 2024 Winter Simulation Conference |
Conference Location: | Orlando, Florida, USA |
Conference Date(s): | 2024-12-15 - 2024-12-18 |
Publisher: | IEEE |
DOI: | 10.1109/wsc63780.2024.10838824 |
Official URL: | https://doi.org/10.1109/wsc63780.2024.10838824 |
Date Deposited: | 24 Sep 2024 16:18 |
Last Modified: | 11 Feb 2025 12:22 |
Cite in APA 7: | Duhem, L., Ben Ali, M., Morin, M., & Gaudreault, J. (2024, December). A comparative study of price-driven production control methods using a sawmill simulator [Paper]. 2024 Winter Simulation Conference, Orlando, Florida, USA. https://doi.org/10.1109/wsc63780.2024.10838824 |
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