Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/195587
Title: Enhancing production and sale based on mathematical statistics and the genetic algorithm
Author: Nestic, Snezana
Aleksic, Aleksandar
Gil Lafuente, Jaime
Ljepava, Nikolina
Keywords: Gestió de la producció
Gestió de vendes
Estadística matemàtica
Algorismes genètics
Production management
Sales management
Mathematical statistics
Genetic algorithms
Issue Date: Apr-2022
Publisher: Univerzitet u Kragujevcu
Abstract: 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.
Note: Reproducció del document publicat a: https://doi.org/10.5937/ekonhor2201057N
It is part of: Ekonomski Horizonti, 2022, vol. 24, num. 1, p. 53-68
URI: http://hdl.handle.net/2445/195587
Related resource: https://doi.org/10.5937/ekonhor2201057N
ISSN: 2217-9232
Appears in Collections:Articles publicats en revistes (Empresa)

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