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Multi-criteria group decision-making method in disposal of municipal solid waste based on cubic Pythagorean fuzzy EDAS approach with incomplete weight information.

Authors :
Paul, Tapas Kumar
Jana, Chiranjibe
Pal, Madhumangal
Source :
Applied Soft Computing; Sep2023, Vol. 144, pN.PAG-N.PAG, 1p
Publication Year :
2023

Abstract

Municipal solid waste management (MSWM) has always been a typical issue in India. The rapid population growth, impetuous adoption of modern lifestyle, and fast urbanization resulted in India's swift generation of complicated municipal solid waste (MSW). Consequently, municipalities of different cities in India face various difficulties in MSW collection, treatment and disposal methodology. Inefficient or poorly managed MSW causes numerous troubles, including air pollution, soil fouling, contamination in drinking water and health hazard, and it also impacts socio-economic deterioration. MSWM technique selection is based on several criteria, which are generally imprecise, uncertain, and vague. This paper uses the cubic Pythagorean fuzzy number to comprise the fuzzy characteristics of the criteria value concerning the five alternatives (Thermochemical methods in MSW treatment and disposal). The best MSW treatment and disposal method is selected amongst the five alternatives under the novel multi-criteria group decision-making (MCGDM) approach, the cubic Pythagorean fuzzy EDAS (Evaluation based on Distance from Average Solution) in the Indian context. The weight information of the criteria has yet to be wholly known. A non-linear optimization scheme is proposed to determine the criteria weights that are partially known to maximize the generalized total distance measure between alternatives corresponding to all criteria. The present method is explained with a case study. Finally, a comparative analysis is drawn between the present and some existing methods, showing that the present method is consistent and robust enough to apply in practice. • CuPyF extended EDAS approach is developed for solving MCGDM problems. • Optimization model is applied for computing incomplete weights. • Create an algorithm for MCGDM problems using the CuP-EDAS technique. • A case study for municipal solid waste management is considered for recycling. • Sensitivity and comparative analysis are verified to validate the results. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15684946
Volume :
144
Database :
Supplemental Index
Journal :
Applied Soft Computing
Publication Type :
Academic Journal
Accession number :
164927060
Full Text :
https://doi.org/10.1016/j.asoc.2023.110515