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Erschienen in: Granular Computing 6/2023

07.10.2023 | Original Paper

Multi-criteria group decision-making for energy production from municipal solid waste in Iran based on spherical fuzzy sets

verfasst von: Kiran Zahid, Muhammad Akram

Erschienen in: Granular Computing | Ausgabe 6/2023

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Abstract

Energy production from the waste is an innovative idea to be implemented that can significantly raise one’s energy production capacity via some adaptable waste-to-energy technology. This study ponders over the municipal solid waste management problem to dispose off the waste in a sanitary, beneficial and environmental friendly manner to reduce the large volume of waste. To target the waste management problem, this article designs a multi-criteria group decision-making technique to capture all the elements of the considered problem within the governance of a decision-making team. The proposed approach, spherical fuzzy ELECTRE III method, has the supplementary potential to delicately treat the pseudo criteria for the authentic investigation of the outranking relations unlike the traditional variants of ELECTRE methods which proceed on the concept of concordance and discordance sets. The proposed technique is privileged to derive the preferences in terms of indifference, strong and weak preference relations by carefully examining the explicit behavior of each criterion in accordance to indifference, preference and veto threshold values. Nextly, this study addresses the case of municipal waste management of the Azerbaijan region in Iran and investigates different waste-to-energy technologies by the proposed SF-ELECTRE III method. To enlighten the consistency of proposed approach, a comparative study with existing SF-PROMETHEE methods is conducted that includes the numerical results and logical arguments.

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Metadaten
Titel
Multi-criteria group decision-making for energy production from municipal solid waste in Iran based on spherical fuzzy sets
verfasst von
Kiran Zahid
Muhammad Akram
Publikationsdatum
07.10.2023
Verlag
Springer International Publishing
Erschienen in
Granular Computing / Ausgabe 6/2023
Print ISSN: 2364-4966
Elektronische ISSN: 2364-4974
DOI
https://doi.org/10.1007/s41066-023-00419-5

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