Preprint Article Version 1 This version is not peer-reviewed

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

Version 1 : Received: 16 September 2019 / Approved: 18 September 2019 / Online: 18 September 2019 (03:32:42 CEST)

A peer-reviewed article of this Preprint also exists.

Ramos-Quintana, F.; Tovar-Sánchez, E.; Saldarriaga-Noreña, H.; Sotelo-Nava, H.; Sánchez-Hernández, J.P.; Castrejón-Godínez, M.-L. A CBR–AHP Hybrid Method to Support the Decision-Making Process in the Selection of Environmental Management Actions. Sustainability 2019, 11, 5649. Ramos-Quintana, F.; Tovar-Sánchez, E.; Saldarriaga-Noreña, H.; Sotelo-Nava, H.; Sánchez-Hernández, J.P.; Castrejón-Godínez, M.-L. A CBR–AHP Hybrid Method to Support the Decision-Making Process in the Selection of Environmental Management Actions. Sustainability 2019, 11, 5649.

Journal reference: Sustainability 2019, 11, 5649
DOI: 10.3390/su11205649

Abstract

This paper proposes a Case-Based Reasoning (CBR) system to contribute to reinforce the sustainable performance of an environmental management system. The CBR system aims to support the decision-making process to select environmental management actions aimed at reducing risky trends of the environmental state of a region. The CBR system 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 the following key environmental variables: CO2 emissions, Air-Quality, Loss of Vegetation Cover, Water Availability, and Solid Waste, whose combination damage the environmental state quality of a region. Meanwhile, solutions are represented by a set of environmental management actions. 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. We used risky trends derived from real data related to the environmental states of a Mexican region to test the proposed CBR system. The results obtained provided insights into the potential of CBR systems to support the decision-making process to select environmental management actions aimed at reducing risky trends of current environmental states.

Subject Areas

decision support systems; environmental state; Case Based Reasoning; Analytic Hierarchy Process; environmental management actions; driving-force variables; pressure variables

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