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Article

An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production

1
Department of Industrial Engineering, Ankara Yıldırım Beyazıt University, Ankara 06010, Turkey
2
Department of Agricultural Biotechnology, Faculty of Agriculture, Tekirdag Namık Kemal University, D.alti, Tekirdağ 59070, Turkey
*
Author to whom correspondence should be addressed.
Academic Editor: Donato Morea
Sustainability 2022, 14(8), 4835; https://doi.org/10.3390/su14084835
Received: 13 February 2022 / Revised: 31 March 2022 / Accepted: 4 April 2022 / Published: 18 April 2022
A hybrid model was developed by combining multiple-criteria decision-making (MCDM) with the analytic hierarchy process (AHP) and a fuzzy set to give decision support for choosing sustainable solutions to agricultural problems. Six steps were taken to build the suggested hybrid model: identifying and weighing criteria; normalizing data using fuzzy membership functions; calculating the weighting of the criteria using AHP; and selecting the best alternative for the agricultural problem. The objective of this case study is to demonstrate how agricultural production techniques (APTs) are becoming more complex as agricultural production becomes more complex. Organic agriculture aims to protect both the environment and consumer satisfaction by utilizing organic management practices that do not have the negative effects associated with conventional and genetic engineering production. Meanwhile, products obtained through conventional and genetic engineering techniques are more cost-effective. To present the superiority of the proposed fuzzy MCDM hybrid model, this problem is used as the causative agent’s dataset. Because the challenge involves a large number of competing quantitative and qualitative criteria, the assessment approach should improve the ratio of input data to output data. As a result, agricultural productivity should be controlled holistically. However, because the problem may contain both qualitative and quantitative facts and uncertainties, it is necessary to represent the uncertainty inherent in human thinking. To achieve superior outcomes, fuzzy set theory (FST), which enables the expression of uncertainty in human judgments, can be integrated with). The purpose of this study is to present a novel MCDM approach based on fuzzy numbers for analyzing decision-making scenarios. The proposed methodology, which is based on Buckley’s fuzzy analytic hierarchy process (B-FAHP) and the Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (F-TOPSIS), uses Buckley’s fuzzy analytic hierarchy process (B-FAHP) and fuzzy TOPSIS to determine weights and rank alternatives, respectively. As a result, we attempted to include both the uncertainty and hesitancy of experts in the decision-making process through the use of fuzzy numbers. We have three main criteria in this study: Satisfaction (C1), Economy (C2), and Environment (C3). An important objective of the current research is to build a complete framework for evaluating and grading the suitability of technologies. A real-world case study is used to demonstrate the suggested paradigm’s validity. View Full-Text
Keywords: multiple-criteria decision-making (MCDM); Buckley’s fuzzy analytic hierarchy process (B-FAHP); fuzzy TOPSIS (F-TOPSIS); agricultural production technique (APT); agriculture problems (AP) multiple-criteria decision-making (MCDM); Buckley’s fuzzy analytic hierarchy process (B-FAHP); fuzzy TOPSIS (F-TOPSIS); agricultural production technique (APT); agriculture problems (AP)
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MDPI and ACS Style

Rouyendegh, B.D.; Savalan, Ş. An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production. Sustainability 2022, 14, 4835. https://doi.org/10.3390/su14084835

AMA Style

Rouyendegh BD, Savalan Ş. An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production. Sustainability. 2022; 14(8):4835. https://doi.org/10.3390/su14084835

Chicago/Turabian Style

Rouyendegh, Babak Daneshvar, and Şeyda Savalan. 2022. "An Integrated Fuzzy MCDM Hybrid Methodology to Analyze Agricultural Production" Sustainability 14, no. 8: 4835. https://doi.org/10.3390/su14084835

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