Enhancing production and sale based on mathematical statistics and the genetic algorithm

Enhancing production and sale has a very significant effect on the competitive advantage of any production enterprise. In practice, especially in companies with highly diversified production, products have a different impact on generating revenue. Therefore, operational management pay attention to t...

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Detalhes bibliográficos
Autores: Nestic, Snezana, Aleksic, Aleksandar, Gil Lafuente, Jaime, Ljepava, Nikolina
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2022
País:España
Recursos:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repositorio:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:2445/195587
Acesso em linha:https://hdl.handle.net/2445/195587
Access Level:acceso abierto
Palavra-chave:Gestió de la producció
Gestió de vendes
Estadística matemàtica
Algorismes genètics
Production management
Sales management
Mathematical statistics
Genetic algorithms
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repository_id_str
spelling Enhancing production and sale based on mathematical statistics and the genetic algorithmNestic, SnezanaAleksic, AleksandarGil Lafuente, JaimeLjepava, NikolinaGestió de la produccióGestió de vendesEstadística matemàticaAlgorismes genèticsProduction managementSales managementMathematical statisticsGenetic algorithmsEnhancing production and sale has a very significant effect on the competitive advantage of any production enterprise. In practice, especially in companies with highly diversified production, products have a different impact on generating revenue. Therefore, operational management pay attention to the products of the utmost importance. The Pareto analysis is the most broadly used product classification method. It can be said that the results obtained by this analysis are still very burdened by decision-makers' subjective attitudes. This paper proposes a model for selecting products with the biggest impact on generating revenue in an exact way. In the model's first stage, whether there is a linear relationship between volume demand and a discounted amount is analyzed applying mathematical statistics methods. In the second stage, the Genetic Algorithm (GA) method is proposed so as to obtain a near-optimal set of the most important products. The proposed model is shown to be a useful and effective assessment tool for sales and operational management in a production enterprise.Univerzitet u Kragujevcu2023202320222023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion16 p.application/pdfhttps://hdl.handle.net/2445/195587Articles publicats en revistes (Empresa)reponame:Recercat. Dipósit de la Recerca de Catalunyainstname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)InglésReproducció del document publicat a: https://doi.org/10.5937/ekonhor2201057NEkonomski Horizonti, 2022, vol. 24, num. 1, p. 53-68https://doi.org/10.5937/ekonhor2201057Ncc-by-nc-nd (c) Univerzitet u Kragujevcu, 2022https://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:recercat.cat:2445/1955872026-05-29T05:05:01Z
dc.title.none.fl_str_mv Enhancing production and sale based on mathematical statistics and the genetic algorithm
title Enhancing production and sale based on mathematical statistics and the genetic algorithm
spellingShingle Enhancing production and sale based on mathematical statistics and the genetic algorithm
Nestic, Snezana
Gestió de la producció
Gestió de vendes
Estadística matemàtica
Algorismes genètics
Production management
Sales management
Mathematical statistics
Genetic algorithms
title_short Enhancing production and sale based on mathematical statistics and the genetic algorithm
title_full Enhancing production and sale based on mathematical statistics and the genetic algorithm
title_fullStr Enhancing production and sale based on mathematical statistics and the genetic algorithm
title_full_unstemmed Enhancing production and sale based on mathematical statistics and the genetic algorithm
title_sort Enhancing production and sale based on mathematical statistics and the genetic algorithm
dc.creator.none.fl_str_mv Nestic, Snezana
Aleksic, Aleksandar
Gil Lafuente, Jaime
Ljepava, Nikolina
author Nestic, Snezana
author_facet Nestic, Snezana
Aleksic, Aleksandar
Gil Lafuente, Jaime
Ljepava, Nikolina
author_role author
author2 Aleksic, Aleksandar
Gil Lafuente, Jaime
Ljepava, Nikolina
author2_role author
author
author
dc.subject.none.fl_str_mv Gestió de la producció
Gestió de vendes
Estadística matemàtica
Algorismes genètics
Production management
Sales management
Mathematical statistics
Genetic algorithms
topic Gestió de la producció
Gestió de vendes
Estadística matemàtica
Algorismes genètics
Production management
Sales management
Mathematical statistics
Genetic algorithms
description Enhancing production and sale has a very significant effect on the competitive advantage of any production enterprise. In practice, especially in companies with highly diversified production, products have a different impact on generating revenue. Therefore, operational management pay attention to the products of the utmost importance. The Pareto analysis is the most broadly used product classification method. It can be said that the results obtained by this analysis are still very burdened by decision-makers' subjective attitudes. This paper proposes a model for selecting products with the biggest impact on generating revenue in an exact way. In the model's first stage, whether there is a linear relationship between volume demand and a discounted amount is analyzed applying mathematical statistics methods. In the second stage, the Genetic Algorithm (GA) method is proposed so as to obtain a near-optimal set of the most important products. The proposed model is shown to be a useful and effective assessment tool for sales and operational management in a production enterprise.
publishDate 2022
dc.date.none.fl_str_mv 2022
2023
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://hdl.handle.net/2445/195587
url https://hdl.handle.net/2445/195587
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.5937/ekonhor2201057N
Ekonomski Horizonti, 2022, vol. 24, num. 1, p. 53-68
https://doi.org/10.5937/ekonhor2201057N
dc.rights.none.fl_str_mv cc-by-nc-nd (c) Univerzitet u Kragujevcu, 2022
https://creativecommons.org/licenses/by-nc-nd/4.0/
info:eu-repo/semantics/openAccess
rights_invalid_str_mv cc-by-nc-nd (c) Univerzitet u Kragujevcu, 2022
https://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 16 p.
application/pdf
dc.publisher.none.fl_str_mv Univerzitet u Kragujevcu
publisher.none.fl_str_mv Univerzitet u Kragujevcu
dc.source.none.fl_str_mv Articles publicats en revistes (Empresa)
reponame:Recercat. Dipósit de la Recerca de Catalunya
instname:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
instname_str Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
reponame_str Recercat. Dipósit de la Recerca de Catalunya
collection Recercat. Dipósit de la Recerca de Catalunya
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.198674

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