Application of Analytic Hierarchy Process Considering Artificial Neural Network and ARIMA for Selecting a Chemical Waste Plant

Abstract

This study defines the best model for a chemical waste plant where the Artificial Neural Network (ANN) and the Integrated Auto Regressive Moving Average Model (ARIMA) were applied as tools for predicting future maintenance cost data. These methods were applied together considering the criteria as follows: plant size, process cost, treatment flexibility, environmental safety and maintenance cost. For this, a decision-making model was developed using the Hierarchical Analysis Method (AHP) with which the company can decide from three alternatives of waste plant models. As a result, the recommendation and solution provide by the multicriteria method was the choice of the alternative 3 of a waste center. This solution indicated the best alternative considering the criteria selected by the company and also the data from RNA and ARIMA In this case, the model presented an index above 70% both in the final aggregation and in the sensitivity analysis.