An integrated bipolar picture fuzzy decision driven system to scrutinize foodwaste treatment technology through assorted factor analysis
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info:eu-repo/semantics/openAccessAttribution 4.0 InternationalDate
2024Author
Devi, Navaneethakrishnan Suganthi KeerthanaNarayanamoorthy, Samayan
Parthasarathy, Thirumalai Nallasivan
Thilagasree, Chakkarapani Sumathi
Pamucar, Dragan
Simic, Vladimir
Dinçer, Hasan
Yüksel, Serhat
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Devi, N. S. K., Narayanamoorthy, S., Parthasarathy, T. N., Thilagasree, C. S., Pamucar, D., Simic, V. ... Yüksel, S. (2024). An integrated bipolar picture fuzzy decision driven system to scrutinize foodwaste treatment technology through assorted factor analysis. CMES - Computer Modeling in Engineering and Sciences, 140(3), 2665-2687. http://dx.doi.org/10.32604/cmes.2024.050954Abstract
Food Waste (FW) is a pressing environmental concern that affects every country globally. About one-third of the food that is produced ends up as waste, contributing to the carbon footprint. Hence, the FW must be properly treated to reduce environmental pollution. This study evaluates a few available Food Waste Treatment (FWT) technologies, such as anaerobic digestion, composting, landfill, and incineration, which are widely used. A Bipolar Picture Fuzzy Set (BPFS) is proposed to deal with the ambiguity and uncertainty that arise when converting a realworld problem to a mathematical model. A novel Criteria Importance Through Intercriteria Correlation-Stable Preference Ordering Towards Ideal Solution (CRITIC-SPOTIS) approach is developed to objectively analyze FWT selection based on thirteen criteria covering the industry's technical, environmental, and entrepreneurial aspects. The CRITIC method is used for the objective analysis of the importance of each criterion in FWT selection. The SPOTIS method is adopted to rank the alternative hassle-free, following the criteria. The proposed model offers a rank reversal-freemodel, i.e., the rank of the alternatives remains unaffected even after the addition or removal of an alternative. In addition, comparative and sensitivity analyses are performed to ensure the reliability and robustness of the proposed model and to validate the proposed result.
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CMES - Computer Modeling in Engineering and SciencesVolume
140Issue
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