Bibliographic citations
Julca, G., Malca, A., Saravia, J. (2016). Modelo de programación lineal entera para mejorar la productividad del proceso de obtención y procesamiento de la goma de tara de industria Nativa S.A.C. [Trabajo de suficiencia profesional, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/621513
Julca, G., Malca, A., Saravia, J. Modelo de programación lineal entera para mejorar la productividad del proceso de obtención y procesamiento de la goma de tara de industria Nativa S.A.C. [Trabajo de suficiencia profesional]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2016. http://hdl.handle.net/10757/621513
@misc{renati/365292,
title = "Modelo de programación lineal entera para mejorar la productividad del proceso de obtención y procesamiento de la goma de tara de industria Nativa S.A.C.",
author = "Saravia Candiotti, Janiss Mercedes",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2016"
}
This professional sufficiency investigation work, seeks to establish a integer linear programming model to improve the productivity of the process of obtaining and processing Tara Gum for Industria Nativa S.A.C. company. Industria Nativa S.A.C. is a peruvian company whose business is the manufacture of grain mill products, being one of the main agricultural products sold by them the Tara Gum. The company currently has an antique Comprehension Air machine that polluter part of the production of Tara Gum, limits the amount on kilos they should get and waste more energy, which is reflected in the company expenses and reduces the utility that could be obtained from the product. That is why according to the analysis of the different variables of the case, in the research we used the integer linear programming model through the Simplex Method with the aim of proposing a model to help optimize the productivity of tara gum, being a fundamental part of this improvement, and according to the financial analysis of the company, using two shifts in production. Using the integer linear programming, variables and constraints used in its formulation, quantitatively demonstrates the benefits of the model, which will be reflected in the financial statements of the company.
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