The cost of electricity in hospitals represents a significant portion in its context of operating expenses. Therefore, it is important to constantly think about ways to reduce this cost without losing the quality and reliability required for hospital care activity. It is well known, that reducing electricity consumption has a direct impact on the effective management of hospital cash flow, so it is imperative to rationalize this resource. In this context, the objective of this paper focuses on analyzing the economic feasibility of purchasing and using a diesel generator to find the peak hour demand and verifying financial uncertainty by applying a Monte Carlo simulation approach to risk analysis. The target hospital of this research is located in southeastern of Brazil and it is part of a foundation that covers educational and assistance activities, serving the local population and thousands of patients during the year. Finally, the economic risk analysis applied through the Monte Carlo simulation found that the acquisition of the aforementioned diesel generator has a very high probability of viability. Therefore, it is verified that the investment is viable and attractive from the hospital's economic and operational point of view, while the Net Present Value remains positive, with the expected value of R$ 868,358.84, considering the risk and uncertainty analysis having an attractive internal returning rate of 78.76% per year.
Portfolio optimization is a term that can be understood as a problem whose main object is to encounter the most appropriate way to allocate the assets so that maximum returns and the smallest variability can be obtained (Garg & Deep, 2019). Markowitz first introduced the mean variance model in which the risk of the model is defined as the variance of the returns and nowadays many optimization portfolio studies are encountered in the literature (
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