A CBR–AHP Hybrid Method to Support the Decision-Making Process in the Selection of Environmental Management Actions

Abstract

This paper proposes a hybrid method integrating case-based reasoning (CBR) and analytic hierarchy process (AHP) methods to reinforce the sustainable performance of an environmental management system. The CBR–AHP method aims to support the decision-making process to select environmental management actions (EMAs) aimed at reducing risky trends of the environmental state of a region. The CBR methods takes advantage of a set of situation–solution pairs called cases, which are stored in a memory and then retrieved as candidates to solve new problems. Situations in this work are represented by a set of risky trends of key environmental pathways (KEPs) related to CO2 emissions, air quality, loss of vegetation cover, water availability, and solid waste, the combination of which damage the environmental state quality of a region. Meanwhile, solutions are represented by a set of EMAs. Similar situations to a given current situation are retrieved from the memory of cases, and then their solutions are combined through an adaptation mechanism, until the solution of the current problem is obtained. The AHP method is used to assign weights to environmental variables and to alternative solutions represented by EMAs. We used risky trends derived from real data related to the environmental states of a Mexican region to test the proposed CBR–AHP hybrid method. The results obtained provided insights into the potential of the CBR–AHP hybrid method to support the decision-making process to select EMAs aimed at reducing risky trends of current environmental states.