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Fuzzy Hybrid MCDM Model for Ranking the Agricultural Water Demand Management Strategies in Arid Areas

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  • Mohammad Ebrahim Banihabib

    (University college of Aburaihan, University of Tehran)

  • Mohammad Hadi Shabestari

    (University College of Aburaihan, University of Tehran)

Abstract

In this paper, a fuzzy Multi Criteria Decision Making (MCDM) model is proposed for considering the uncertainty of expert’s opinion in decision making of agricultural water demand management. The performance of Analytical Hierarchy Process (AHP) model was evaluated, and the hybrid model of Modified Technique for Order of Preference by Similarity to Ideal Solution (MTOPSIS) and AHP are introduced in non-fuzzy, MTOPSIS-AHP (MTAHP), and Fuzzy MTOPSIS-AHP (FMTAHP) setting, and the result of them were compared. Sensitivity analyses of tested fuzzy MCDM model was carried out in 3 separate steps of aggregation of individual fuzzy judgments, fuzzy distances values for fuzzification and ranking of fuzzy numbers. In this research, Coefficient of Variation (CV) index of final rates was proposed to evaluate the performance of MCDM models. The results of this paper showed that the geometric mean method is better for aggregation of individual fuzzy judgments. The results showed that non-fuzzy proposed model, MTAHP provided better ranking resolution among tested non-fuzzy MCDM models and only the proposed FMTAHP model significantly increased the CV index of final rates and improve the results resolution. Finally, the proposed MTAHP and FMTAHP models introduced as the best models for ranking alternatives by high resolution in non-fuzzy and fuzzy environment, respectively.

Suggested Citation

  • Mohammad Ebrahim Banihabib & Mohammad Hadi Shabestari, 2017. "Fuzzy Hybrid MCDM Model for Ranking the Agricultural Water Demand Management Strategies in Arid Areas," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(1), pages 495-513, January.
    • Handle: RePEc:spr:waterr:v:31:y:2017:i:1:d:10.1007_s11269-016-1544-y
    DOI: 10.1007/s11269-016-1544-y
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    Cited by:

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    2. Mirzaie, Nargis & Banihabib, Mohammad Ebrahim & shahdany, S. Mehdy hashemy & Randhir, Timothy O., 2021. "Fuzzy particle swarm optimization for conjunctive use of groundwater and reclaimed wastewater under uncertainty," Agricultural Water Management, Elsevier, vol. 256(C).
    3. Mohammad Ebrahim Banihabib & Mahmoud Mohammad Rezapour Tabari & Mohsen Mohammad Rezapour Tabari, 2019. "Development of a Fuzzy Multi-Objective Heuristic Model for Optimum Water Allocation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(11), pages 3673-3689, September.
    4. Babak Zolghadr-Asli & Omid Bozorg-Haddad & Maedeh Enayati & Xuefeng Chu, 2021. "A review of 20-year applications of multi-attribute decision-making in environmental and water resources planning and management," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(10), pages 14379-14404, October.
    5. Abbas Roozbahani & Ebrahim Ebrahimi & Mohammad Ebrahim Banihabib, 2018. "A Framework for Ground Water Management Based on Bayesian Network and MCDM Techniques," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(15), pages 4985-5005, December.
    6. Seyed Farhan Moosavian & Daryoosh Borzuei & Abolfazl Ahmadi, 2022. "Cost Analysis of Water Quality Assessment Using Multi-Criteria Decision-Making Approach," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(12), pages 4843-4862, September.
    7. Avijit De & Sujit Das & Samarjit Kar, 2021. "Ranking of interval type 2 fuzzy numbers using correlation coefficient and Mellin transform," OPSEARCH, Springer;Operational Research Society of India, vol. 58(4), pages 1018-1048, December.

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