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

Author

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  • Fernando Ramos-Quintana

    (Dirección General de Desarrollo Sustentable, Universidad Autónoma del Estado de Morelos, Av. Universidad 1001, Cuernavaca, Morelos 62209, Mexico)

  • Efraín Tovar-Sánchez

    (Centro de Investigación en Biodiversidad y Conservación, Universidad Autónoma del Estado de Morelos, Av. Universidad 1001, Cuernavaca, Morelos 62209, Mexico)

  • Hugo Saldarriaga-Noreña

    (Centro de Investigaciones Químicas, Instituto de Ciencias Básicas y Aplicadas, Universidad Autónoma del Estado de Morelos, Av. Universidad 1001, Cuernavaca, Morelos 62209, Mexico)

  • Héctor Sotelo-Nava

    (Dirección General de Desarrollo Sustentable, Universidad Autónoma del Estado de Morelos, Av. Universidad 1001, Cuernavaca, Morelos 62209, Mexico)

  • Juan Paulo Sánchez-Hernández

    (Dirección de Informática, Electrónica y Telecomunicaciones, Universidad Politécnica de Estado de Morelos, Boulevard Cuauhnáhuac 566, Jiutepec, Morelos 62550, Mexico)

  • María-Luisa Castrejón-Godínez

    (Dirección General de Desarrollo Sustentable, Universidad Autónoma del Estado de Morelos, Av. Universidad 1001, Cuernavaca, Morelos 62209, Mexico)

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 CO 2 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.

Suggested Citation

  • Fernando Ramos-Quintana & Efraín Tovar-Sánchez & Hugo Saldarriaga-Noreña & Héctor Sotelo-Nava & Juan Paulo Sánchez-Hernández & María-Luisa Castrejón-Godínez, 2019. "A CBR–AHP Hybrid Method to Support the Decision-Making Process in the Selection of Environmental Management Actions," Sustainability, MDPI, vol. 11(20), pages 1-30, October.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:20:p:5649-:d:276130
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    1. Yi Liang & Dongxiao Niu & Haichao Wang & Yan Li, 2017. "Factors Affecting Transportation Sector CO 2 Emissions Growth in China: An LMDI Decomposition Analysis," Sustainability, MDPI, vol. 9(10), pages 1-20, September.
    2. Alix-Garcia, Jennifer Marie & de Janvry, Alain & Sadoulet, Elisabeth, 2004. "Payments for Environmental Services: To whom, where, and how much?," 2004 Annual meeting, August 1-4, Denver, CO 20421, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    3. Maxim, Laura & Spangenberg, Joachim H. & O'Connor, Martin, 2009. "An analysis of risks for biodiversity under the DPSIR framework," Ecological Economics, Elsevier, vol. 69(1), pages 12-23, November.
    4. Ho, William & Xu, Xiaowei & Dey, Prasanta K., 2010. "Multi-criteria decision making approaches for supplier evaluation and selection: A literature review," European Journal of Operational Research, Elsevier, vol. 202(1), pages 16-24, April.
    5. Cecilia Tortajada, 2006. "Who Has Access to Water? Case Study of Mexico City Metropolitan Area," Human Development Occasional Papers (1992-2007) HDOCPA-2006-16, Human Development Report Office (HDRO), United Nations Development Programme (UNDP).
    6. Timilsina, Govinda R. & Shrestha, Ashish, 2009. "Why have CO2 emissions increased in the transport sector in Asia ? underlying factors and policy options," Policy Research Working Paper Series 5098, The World Bank.
    7. Timilsina, Govinda R. & Shrestha, Ashish, 2009. "Transport sector CO2 emissions growth in Asia: Underlying factors and policy options," Energy Policy, Elsevier, vol. 37(11), pages 4523-4539, November.
    8. Fernando Ramos-Quintana & Héctor Sotelo-Nava & Hugo Saldarriaga-Noreña & Efraín Tovar-Sánchez, 2019. "Assessing the Environmental Quality Resulting from Damages to Human-Nature Interactions Caused by Population Increase: A Systems Thinking Approach," Sustainability, MDPI, vol. 11(7), pages 1-29, April.
    9. Chen, Serena H. & Jakeman, Anthony J. & Norton, John P., 2008. "Artificial Intelligence techniques: An introduction to their use for modelling environmental systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 379-400.
    10. Knapp, Tom & Mookerjee, Rajen, 1996. "Population growth and global CO2 emissions : A secular perspective," Energy Policy, Elsevier, vol. 24(1), pages 31-37, January.
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