Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.

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 sam...

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Autores principales:	José Emmanuel Gómez-Rocha, Eva Selene Hernández-Gress, Héctor Rivera-Gómez
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/4a9a6aa71af941dfb24c5410fc328ee9
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spelling	oai:doaj.org-article:4a9a6aa71af941dfb24c5410fc328ee92021-12-02T20:10:42ZProduction planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.1932-620310.1371/journal.pone.0252801https://doaj.org/article/4a9a6aa71af941dfb24c5410fc328ee92021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0252801https://doaj.org/toc/1932-6203In 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.José Emmanuel Gómez-RochaEva Selene Hernández-GressHéctor Rivera-GómezPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 6, p e0252801 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q José Emmanuel Gómez-Rocha Eva Selene Hernández-Gress Héctor Rivera-Gómez Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.
description	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.
format	article
author	José Emmanuel Gómez-Rocha Eva Selene Hernández-Gress Héctor Rivera-Gómez
author_facet	José Emmanuel Gómez-Rocha Eva Selene Hernández-Gress Héctor Rivera-Gómez
author_sort	José Emmanuel Gómez-Rocha
title	Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.
title_short	Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.
title_full	Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.
title_fullStr	Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.
title_full_unstemmed	Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.
title_sort	production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/4a9a6aa71af941dfb24c5410fc328ee9
work_keys_str_mv	AT joseemmanuelgomezrocha productionplanningofafurnituremanufacturingcompanywithrandomdemandandproductioncapacityusingstochasticprogramming AT evaselenehernandezgress productionplanningofafurnituremanufacturingcompanywithrandomdemandandproductioncapacityusingstochasticprogramming AT hectorriveragomez productionplanningofafurnituremanufacturingcompanywithrandomdemandandproductioncapacityusingstochasticprogramming
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Production planning of a furniture manufacturing company with random demand and production capacity using stochastic programming.

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