Cost Optimization in Latin American Companies with Genetic Algorithms during 2015-2023 ; Optimización de Costos en Empresas Latinoamericanas con Algoritmos Genéticos durante 2015-2023
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| Názov: | Cost Optimization in Latin American Companies with Genetic Algorithms during 2015-2023 ; Optimización de Costos en Empresas Latinoamericanas con Algoritmos Genéticos durante 2015-2023 |
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| Autori: | Kwan Chung, Chap Kau, Alegre Brítez, Miguel Ángel |
| Zdroj: | Espíritu Emprendedor TES; Vol. 9 No. 1 (2025): ESPÍRITU EMPRENDEDOR TES; 1-12 ; Espíritu Emprendedor TES; Vol. 9 Núm. 1 (2025): ESPÍRITU EMPRENDEDOR TES; 1-12 ; 2602-8093 ; 10.33970/eetes.v9.n1.2025 |
| Informácie o vydavateľovi: | Instituto Superior Tecnológico Espíritu Santo, con Condición de Universitario |
| Rok vydania: | 2025 |
| Predmety: | genetic algorithms, cost optimization, cost accounting, Latin American companies, automation, Problem: Cost accounting in Latin American companies faces the challenge of managing large volumes of data and performing accurate analysis in a volatile economic environment. The difficulty lies in the efficient management of indirect costs and real-time decision making, exacerbated by economic fluctuations and competitive pressures. General objective: To evaluate the effectiveness of evolutionary algorithms, especially genetic algorithms, in optimizing accounting and financial processes in Latin American companies during the period 2015-2023. The aim is to improve resource allocation and cost management accuracy to meet current economic challenges. Brief methodology: A genetic algorithm was implemented to minimize unit cost in production processes. Simulated data on indirect costs and units produced were used, the algorithm simulates selection, crossing, and mutation processes to find optimal solutions. An initial population of solutions was generated, the fitness of each solution was evaluated, and selection, and mutation techniques were applied over 50 generations to obtain the best resource allocation. Key findings: The genetic algorithm proved to be effective in minimizing unit cost by optimizing resource allocation. The generated solutions showed a significant reduction in unit costs compared to traditional methods. Automation and accuracy in data analysis improved, providing companies with more useful information for decision making. Key findings: The adoption of evolutionary algorithms in cost accounting offers significant advantages in terms of efficiency and accuracy in the financial management of Latin American companies. Although there are barriers such as the need for investment in technology and training, and resistance to change, evolutionary algorithms have the potential to transform accounting processes by automating and optimizing decision making. This translates into a competitive advantage in a challenging economic environment, improving the profitability and adaptability of companies, algoritmos genéticos, optimización de costos, contabilidad de costos, empresas latinoamericanas, automatizacion |
| Popis: | Problem: Cost accounting in Latin American companies faces the challenge of managing large volumes of data and performing accurate analysis in a volatile economic environment. The difficulty lies in the efficient management of indirect costs and real-time decision making, exacerbated by economic fluctuations and competitive pressures. General objective: To evaluate the effectiveness of evolutionary algorithms, especially genetic algorithms, in optimizing accounting and financial processes in Latin American companies during the period 2015-2023. The aim is to improve resource allocation and cost management accuracy to meet current economic challenges. Brief methodology: A genetic algorithm was implemented to minimize unit cost in production processes. Simulated data on indirect costs and units produced were used; the algorithm simulates selection, crossing, and mutation processes to find optimal solutions. An initial population of solutions was generated, the fitness of each solution was evaluated, and selection, crossing, and mutation techniques were applied over 50 generations to obtain the best resource allocation. Key findings: The genetic algorithm proved to be effective in minimizing unit cost by optimizing resource allocation. The generated solutions showed a significant reduction in unit costs compared to traditional methods. Automation and accuracy in data analysis improved, providing companies with more useful information for decision making. Key findings: The adoption of evolutionary algorithms in cost accounting offers significant advantages in terms of efficiency and accuracy in the financial management of Latin American companies. Although there are barriers such as the need for investment in technology and training, and resistance to change, evolutionary algorithms have the potential to transform accounting processes by automating and optimizing decision making. This translates into a competitive advantage in a challenging economic environment, improving the profitability and adaptability of ... |
| Druh dokumentu: | article in journal/newspaper |
| Popis súboru: | application/pdf; text/html |
| Jazyk: | Spanish; Castilian |
| Relation: | https://www.espirituemprendedortes.com/index.php/revista/article/view/413/549; https://www.espirituemprendedortes.com/index.php/revista/article/view/413/550; https://www.espirituemprendedortes.com/index.php/revista/article/view/413 |
| DOI: | 10.33970/eetes.v9.n1.2025.413 |
| Dostupnosť: | https://www.espirituemprendedortes.com/index.php/revista/article/view/413 https://doi.org/10.33970/eetes.v9.n1.2025.413 |
| Rights: | Derechos de autor 2025 Chap Kau Kwan Chung, Miguel Ángel Alegre Brítez ; https://creativecommons.org/licenses/by-nc-nd/4.0 |
| Prístupové číslo: | edsbas.41FA2FFA |
| Databáza: | BASE |
Nájsť tento článok vo Web of Science | Abstrakt: | Problem: Cost accounting in Latin American companies faces the challenge of managing large volumes of data and performing accurate analysis in a volatile economic environment. The difficulty lies in the efficient management of indirect costs and real-time decision making, exacerbated by economic fluctuations and competitive pressures. General objective: To evaluate the effectiveness of evolutionary algorithms, especially genetic algorithms, in optimizing accounting and financial processes in Latin American companies during the period 2015-2023. The aim is to improve resource allocation and cost management accuracy to meet current economic challenges. Brief methodology: A genetic algorithm was implemented to minimize unit cost in production processes. Simulated data on indirect costs and units produced were used; the algorithm simulates selection, crossing, and mutation processes to find optimal solutions. An initial population of solutions was generated, the fitness of each solution was evaluated, and selection, crossing, and mutation techniques were applied over 50 generations to obtain the best resource allocation. Key findings: The genetic algorithm proved to be effective in minimizing unit cost by optimizing resource allocation. The generated solutions showed a significant reduction in unit costs compared to traditional methods. Automation and accuracy in data analysis improved, providing companies with more useful information for decision making. Key findings: The adoption of evolutionary algorithms in cost accounting offers significant advantages in terms of efficiency and accuracy in the financial management of Latin American companies. Although there are barriers such as the need for investment in technology and training, and resistance to change, evolutionary algorithms have the potential to transform accounting processes by automating and optimizing decision making. This translates into a competitive advantage in a challenging economic environment, improving the profitability and adaptability of ... |
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| DOI: | 10.33970/eetes.v9.n1.2025.413 |