Predictive studies of solid waste production capacity in fast food restaurants using the bootstrap method and time series

Abstract

Fast food restaurants are responsible for much of the solid waste produced in Brazil. The management of these wastes has a such fundamental importance, because the environmental impact caused by its inadequacy causes incalculable damage to the environment. The performance of the solid waste management system can be determined by evaluating your service level. In restaurants, the level of solid waste service is determined based on the quantity generated. Therefore, the objective of this study was to develop a statistical planning to explore the predictability of the amount of solid waste generated in a fast food restaurant, aiming to develop a monitoring system, based on sustainability indexes, increasing knowledge about the relevant processes and possible internal barriers. Thus, a computational routine was created in the C++ language through the bootstrap statistical method. The results showed that the bootstrap method is a robust statistical tool to predict the amount of solid waste generated in fast food restaurants. The use of time series was important for comparative studies with the data obtained by the bootstrap method, as well as the implementation of a routine predictive analysis of solid waste in a fast food restaurant.