Evaluation of food waste treatment techniques using aczel alsina based MAGDM model in the q-rung orthopair fuzzy soft structure.

Journal: Scientific reports
Published Date:

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 (q-ROFSAAWG) operators are developed with their desirable properties. These operators encourage more accurate and sustainable consolidation of unsure data in multi-attribute group decision-making (MAGDM) mechanisms. A real-life example highlights the proposed method's feasibility and efficacy in identifying the most optimal food waste treatment technologies (FWTT). The comparative study confirms this methodology's validity, exactitude, and feasibility, clarifying its better accuracy and feasibility as compared to other methods. The outcomes demonstrate that the most effective technique for facilitating food waste treatment in the FWM is incineration.

Authors

  • Rana Muhammad Zulqarnain
    Department of Mathematics, School of Science, University of Management and Technology, Sialkot Campus, Lahore, Pakistan.
  • Hongwei Wang
    Department of Oncological Surgery, Harbin Medical University Cancer Hospital, Harbin, 150000, Heilongjiang Province, China.
  • Usman Zulfiqar
    Department of Business Administration, Lahore Leads University, Lahore, Pakistan.
  • Rifaqat Ali
    Department of Mathematics, College of Science and Arts, King Khalid University, Muhayil 61413, Abha, Saudi Arabia.
  • Imran Siddique
    Department of Mathematics, School of Science, University of Management and Technology, Lahore 54770, Pakistan.
  • Abdullatif Saleh Ghallab
    Faculty of Computing and Information Technology, University of Science and Technology, Sana'a, Yemen. ghallab@ust.edu.ye.
  • Hafiz Shahzar Riaz Khan Tareen
    Department of Statistics, Bahauddin Zakariya University, Multan, 60000, Pakistan.
  • Sohaib Abdal
    Department of Mathematics, Saveetha School of Engineering, SIMATS Thandalam, Chennai, Tamilnadu, 602105, India.