Aplicabilidade do método de simulação de Monte Carlo na previsão dos custos de produção de companhias industriais: o caso da Companhia Vale do Rio Doce

Abstract

Autorização concedida ao Repositório da Universidade de Brasília (RIUnB) pelo editor da revista, em 30/11/2010, com os seguintes condições: disponível sob Licença Creative Commons 3.0, que permite copiar, distribuir e transmitir o trabalho, desde que seja citado o autor e licenciante. Não permite o uso para fins comerciais nem a adaptação desta.Authorization granted to the Repository of the University of Brasília (RIUnB) by the editor of the journal, on 30/11/2010, with the following conditions: available under Creative Commons License 3.0, that allows you to copy, distribute and transmit the work, provided the author and the licensor is cited. Does not allow the use for commercial purposes nor adaptation. Lustosa and Oliveira (2007). To verify the predictive ability of the method comparative analysis are performed, using statistical tests of means between the real samples and the post-privatization period simulated samples. The results show the suitability of the method in predicting the production costs and consequently assisting the decisional process.

Sales forecasting in a mechanical component manufacturer: comparison between monte carlo simulation and time series analysis

“…Another question that can be raised is in relation to the results found by Garcia, Lustosa and Barros (2010) and Matias (2006), since both works had smaller amounts of observations and simulations, which raises doubts if the application of other methodologies would not be more accurate and with more significant results. http://www.ijmp.jor.br v. 10, n. 4, Special Edition IFLOG 2018ISSN: 2236 On the other hand, the argument of Donatelli andKorath (2005) andFernandes (2005) is confirmed, since the biggest monthly error estimated by the Monte Carlo occurred in August with a lower forecast of "818,516" units.…”

“…According to Donatelli and Konrath (2005) the best application for the Monte Carlo simulation is in mathematical systems that do not allow an analytical solution due to the unpredictability of the information, since it is a technique with high effectiveness in random statistical sampling. Garcia, Lustosa and Barros (2010) apply the Monte Carlo simulation to predict the cost of production of industrial companies, using 28 entities, and generating 5600 simulations for them. Mendes, Silva and Kawamoto Júnior (2016) used Monte Carlo simulation to analyze the variability in capacity caused by human behavior.…”

Analysis of the economic viability of a rural tourism enterprise in Brazil: an application of the Monte Carlo Method

“…The minimum value found in the simulation for the project's total NPV was R$ 3,102,679.69, which is R$ 2,334,892.87, higher than the sum of the pessimistic NPV. The maximum NPV found in the simulation was R$ 4,358,873.26, which is R$ 748,279.58 According to Garcia et al (2010), the range or amplitude refers to the difference between the maximum and minimum points. However, in the comparison of this work, we can see the great distance between the extreme points of the real values and the simulated ones, as well as the great difference in their amplitudes.…”

Como Melhorar a Aprendizagem em Pesquisa Operacional? Uma Análise do Desempenho de Estudantes de Administração de Empresas e de Contabilidade

“…No Brasil há também vários exemplos de aplicações de Pesquisa Operacional em Administração e Contabilidade (Garcia, 1999;Scalabrin et al, 2006;Zuccolotto e Colodeti Filho, 2007;Campos, 2010;Garcia et al, 2010;Pacheco e Morabito, 2010;Saraiva Jr. et al, 2011;Tavares et al, 2011).…”