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Tytuł:
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Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.
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Autorzy:
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Gómez-Rocha JE; Engineering Academic Area, Universidad Autónoma del Estado de Hidalgo, Pachuca de Soto, Hidalgo, México.
Hernández-Gress ES; School of Engineering and Science, Tecnologico de Monterrey, Pachuca de Soto, Hidalgo, México.
Rivera-Gómez H; Engineering Academic Area, Universidad Autónoma del Estado de Hidalgo, Pachuca de Soto, Hidalgo, México.
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Źródło:
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PloS one [PLoS One] 2021 Jun 14; Vol. 16 (6), pp. e0252801. Date of Electronic Publication: 2021 Jun 14 (Print Publication: 2021).
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Typ publikacji:
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Journal Article
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Język:
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English
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Imprint Name(s):
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Original Publication: San Francisco, CA : Public Library of Science
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MeSH Terms:
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Algorithms*
Models, Theoretical*
Stochastic Processes*
Commerce/*methods
Interior Design and Furnishings/*methods
Commerce/statistics & numerical data ; Computer Simulation ; Humans ; Interior Design and Furnishings/statistics & numerical data ; Mexico ; Reproducibility of Results
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References:
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Arch Dermatol. 2003 Dec;139(12):1614-9; discussion 1619. (PMID: 14676080)
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Molecular Sequence:
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figshare 10.6084/m9.figshare.14444609.v1; 10.6084/m9.figshare.14450430
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Entry Date(s):
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Date Created: 20210614 Date Completed: 20211115 Latest Revision: 20231102
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Update Code:
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20240104
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PubMed Central ID:
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PMC8202929
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DOI:
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10.1371/journal.pone.0252801
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PMID:
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34125852
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In this article two multi-stage stochastic linear programming models are developed, one applying the stochastic programming solver integrated by Lingo 17.0 optimization software that utilizes an approximation using an identical conditional sampling and Latin-hyper-square techniques to reduce the sample variance, associating the probability distributions to normal distributions with defined mean and standard deviation; and a second proposed model with a discrete distribution with 3 values and their respective probabilities of occurrence. In both cases, a scenario tree is generated. The models developed are applied to an aggregate production plan (APP) for a furniture manufacturing company located in the state of Hidalgo, Mexico, which has important clients throughout the country. Production capacity and demand are defined as random variables of the model. The main purpose of this research is to determine a feasible solution to the aggregate production plan in a reasonable computational time. The developed models were compared and analyzed. Moreover, this work was complemented with a sensitivity analysis; varying the percentage of service level, also, varying the stochastic parameters (mean and standard deviation) to test how these variations impact in the solution and decision variables.
Competing Interests: The authors have declared that no competing interests exist.
