El problema de la selección y ordenamiento de proyectos es común en los procesos de planeación de empresas privadas y públicas que tienen la obligación de administrar y asignar recursos usualmente escasos, entre alternativas que difieren en aspectos técnicos, operacionales, financieros, además del nivel de riesgo. Este artículo presenta una aplicación del problema de optimización de portafolios de proyectos en condiciones de incertidumbre y restricción presupuestal. En primer lugar, se aborda el problema utilizando como función objetivo la maximización del valor presente neto esperado (ENPV) del portafolio de proyectos y en segunda instancia se propone como función objetivo la maximización de dos indicadores de riesgo asociados al ENPV del portafolio: Maximizar el NPV del portafolio para un cierto nivel de confianza y maximizar la probabilidad de obtener un portafolio factible en términos económicos. La metodología se desarrolló en el marco de un proyecto de investigación aplicada financiado por una empresa de servicios públicos. Para ilustrar la metodología planteada se hace uso de un ejemplo adaptado, en el cual se supone que la compañía puede asignar recursos en forma parcial a varios proyectos entre un conjunto de alternativas de inversión independientes. Los nuevos desarrollos en el área de la optimización estocástica permiten mejorar la calidad de las decisiones de asignación de recursos financieros limitados, mediante el uso de indicadores de desempeño relacionados en forma directa con la estrategia de la empresa. Los resultados muestran la asignación óptima de recursos financieros a cada proyecto teniendo en cuenta la incertidumbre asociada a las diferentes variables de entrada, las cuales se modelan mediante distribuciones empíricas de probabilidad definidas a priori por el analista.
The problem of selection and management of projects is common in the planning process of private and public companies and is required to manage and allocate scarce resources usually between alternatives that differ in technical, operational, and financial aspects, in addition to the level of risk. This article presents an application of a portfolio optimization problem of projects under uncertainty and budget constraints. Firstly, it addresses the problem using as the objective function the maximization of the Expected Net Present Value (ENPV) of the portfolio of projects. Secondly, the objective function is the maximization of two indicators of risk associated with the portfolio ENPV: Maximizing the Net Present Value (NPV) of the portfolio for a certain level of centainty and maximizing the probability of obtaining a feasible portfolio in economic terms. The methodology was developed in the framework of a research project funded by an utility company. To illustrate the proposed methodology, a suitable example, which assumes that the company can partially allocate resources to several projects from a pool of independent investment alternatives was used. New developments in the area of stochastic optimization can help to improve the quality of decisions to allocate limited financial resources, through the use of performance indicators related directly to the company's strategy. The results show the optimal allocation of financial resources to each project taking into account the uncertainty associated with different input variables, which are mompanies and is required to manage and allocate scarce resources usually between alternatives that differ in technical, operational, and financial aspects, in addition to the level of risk. This article presents an application of a portfolio optimization problem of projects under uncertainty and budget constraints. Firstly, it addresses the problem using as the objective function the maximization of the Expected Net Present Value (ENPV) of the portfolio of projects. Secondly, the objective function is the maximization of two indicators of risk associated with the portfolio ENPV: Maximizing the Net Present Value (NPV) of the portfolio for a certain level of centainty and maximizing the probability of obtaining a feasible portfolio in economic terms. The methodology was developed in the framework of a research project funded by an utility company. To illustrate the proposed methodology, a suitable example, which assumes that the company can partially allocate resources to several projects from a pool of independent investment alternatives was used. New developments in the area of stochastic optimization can help to improve the quality of decisions to allocate limited financial resources, through the use of performance indicators related directly to the company's strategy. The results show the optimal allocation of financial resources to each project taking into account the uncertainty associated with different input variables, which are modeled using empirical probability distributions defined a priori by the analyst.
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