The present research work consists in the development of a method where a mathematical model of a fish canning plant installation project is proposed, considering the investment, the production costs, the operating expenses, the financial statements, and as indicators for decision making, the net financial present value and internal rate of financial return. Then, the mathematical model is optimized using a non-linear programming to choose the most convenient investment alternative, then a Monte Carlo simulation is carried out in which random variables of plant and market are considered that allow the investor to estimate the minimum values and máximum that can happen in the financial indicators and finally the discussion of results.

The present research work consists in the development of a method where a mathematical model of a fish canning plant installation project is proposed, considering the investment, the production costs, the operating expenses, the financial statements, and as indicators for decision making, the net financial present value and internal rate of financial return. Then, the mathematical model is optimized using a non-linear programming to choose the most convenient investment alternative, then a Monte Carlo simulation is carried out in which random variables of plant and market are considered that allow the investor to estimate the minimum values and máximum that can happen in the financial indicators and finally the discussion of results.

La presente tesis doctoral tiene como objetivo implementar un sistema de planeación de materiales que mejore la toma de decisiones en un proyecto de inversión industrial pesquero. El sistema de planeación de materiales considera modelos de pronósticos de la demanda, plan agregado de producción, programa maestro de producción y el plan de requerimientos de materiales dentro de una plantilla de MS Excel®. El proyecto de inversión tiene tres escenarios. El ESCENARIO 1 contiene un sistema de planeación de materiales y el modelo de pronóstico de descomposición de series de tiempo aditivo estacional para la demanda. El ESCENARIO 2 también tiene el mismo sistema de planeación de materiales, pero utiliza datos reales en la proyección de la demanda y el ESCENARIO 3 no tiene el sistema de planeación de materiales, pero utiliza el modelo de tendencia lineal para los pronósticos de l...

In the canned fish production program, it is very important to calculate its forecast through statistical models that minimize the error of the projections and that allow estimating the quantities to be produced. The objective of this research work is to select a forecast model for the consumption of canned fish in Peru for an industrial fishing project using time series models. Prediction models such as linear regression, time series decomposition and Winters’ method were used. The input data was the monthly domestic sales of canned fish from the years 2011 to 2014. The prediction error measures such as the mean absolute deviation (MAD) and the mean absolute percentage error (MAPE) of the prediction of a company were compared for a year (2014), two years (2013-2014), three years (2012-2014) and four years (2011-2014) to validate with the prediction for the years 2015-2019. The predict...