Hybrid Intuitionistic Fuzzy Entropy-SWARA-COPRAS Method for Multi-Criteria Sustainable Biomass Crop Type Selection

Abbas Mardani (), Sarita Devi, Melfi Alrasheedi, Leena Arya, Mrigendra Pratap Singh and Kiran Pandey
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Abbas Mardani: Business School, Worcester Polytechnic Institute, Worcester, MA 01609-2280, USA
Sarita Devi: School of Engineering and Sciences, GD Goenka University, Gurugram 122103, India
Melfi Alrasheedi: Department of Quantitative Methods, School of Business, King Faisal University, Hofuf 31982, Saudi Arabia
Leena Arya: Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram 522302, India
Mrigendra Pratap Singh: Department of Botany, Government College Raigaon, Satna 485441, India
Kiran Pandey: Department of Computer Science and Engineering, Technocrat Institute of Technology, Bhopal 462038, India

Sustainability, 2023, vol. 15, issue 10, 1-18

Abstract: To select a biomass crop type of the highest sustainability for the purpose of producing biofuel is recognized as a problem of the multi-criteria decision analysis (MCDA) type, as it comprises different conflicting criteria. To effectively address this problem, the present paper introduces a novel integrated approach using the complex proportional assessment (COPRAS) method under the intuitionistic fuzzy sets (IFSs). The proposed approach works based on the IFSs operators as well as an innovative process utilized in evaluating the attributes’ weights. To evaluate these weights, the subjective weights using the step-wise weight assessment ratio analysis (SWARA) model are integrated with the objective weights achieved using an entropy-based approach in order to attain more realistic weights. As MCDA problems inevitably suffer from different degrees of uncertainty, the proposed approach could be of great help to those who are required to make decisions in uncertain settings. The paper took into consideration a sustainable biomass crop selection problem to exemplify the effectiveness of the presented approach in handling real MCDA problems. Moreover, a sensitivity analysis with respect to the diverse values of the attributes is presented in order to assess the stability of the introduced model. This study reveals that the combination of the objective and subjective weights enhances the stability of the introduced approach with diverse attribute weights. Finally, the results of the introduced model are compared to some existing intuitionistic fuzzy information-based methods. The findings of the comparison confirm the efficiency of the present approach in performing the defined tasks under uncertain environments.

Keywords: biomass crop; intuitionistic fuzzy sets; entropy; SWARA; COPRAS; MCDA; sustainability; biofuel sector (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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