Evaluation of food waste treatment techniques using aczel alsina based MAGDM model in the q-rung orthopair fuzzy soft structure
Rana Muhammad Zulqarnain, Hongwei Wang, Usman Zulfiqar, Rifaqat Ali, Imran Siddique, Abdullatif Saleh Ghallab, Hafiz Shahzar Riaz Khan Tareen, Sohaib Abdal

TL;DR
This paper introduces a new decision-making model using fuzzy logic to evaluate food waste treatment techniques, aiming to improve accuracy and sustainability.
Contribution
The paper proposes novel Aczel–Alsina aggregation operators within a q-rung orthopair fuzzy soft set framework for multi-attribute group decision-making.
Findings
The proposed model effectively identifies optimal food waste treatment technologies.
Incineration is found to be the most effective technique for food waste management.
The model outperforms existing methods in accuracy and feasibility.
Abstract
Food waste is a major obstacle in managing inequality, optimizing living conditions, and promoting prosperity, specifically among the world’s most starving economies. Its influences stretch to preventing food supply; it alters financial maturation, complicates environmental issues decomposition, and incorporates raised food operating expenses. Monitoring food waste is implicitly challenging due to confusion arising from its authenticity, extent, geographic location, and schedule; all factors prevent decision-making procedures. This research proposes Aczel–Alsina operational laws to solve the obstacles and intrinsic uncertainty in a q-rung orthopair fuzzy soft sets (q-ROFSS) structure. Also, two novel Aczel–Alsina aggregation operators (AOs) such as q-rung orthopair fuzzy soft aczel–alsina weighted average (q-ROFSAAWA) and q-rung orthopair fuzzy soft aczel–alsina weighted geometric…
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Taxonomy
TopicsMulti-Criteria Decision Making · Fuzzy and Soft Set Theory · Optimization and Mathematical Programming
