Issue |
RAIRO-Oper. Res.
Volume 57, Number 3, May-June 2023
|
|
---|---|---|
Page(s) | 1239 - 1265 | |
DOI | https://doi.org/10.1051/ro/2023033 | |
Published online | 14 June 2023 |
Multi-attribute group decision-making for solid waste management using interval-valued q-rung orthopair fuzzy COPRAS
1
Department of Operational Research, University of Delhi, Delhi 110007, India
2
Department of Material and Production, Aalborg University, Fibigerstræde 16, DK 9220 Aalborg East, Denmark
3
Department of Applied Mathematics with Oceanology and Computer Programming, Vidyasagar University, Midnapore 721102, West Bengal, India
* Corresponding author: sankroy2006@gmail.com
Received:
11
December
2022
Accepted:
15
March
2023
In this paper, the COPRAS (Complex Proportional Assessment) method is extended for interval-valued q-rung orthopair fuzzy numbers (IVq-ROFNs) to solve multi-attribute group decision-making (MAGDM) problems. A novel distance measure for IVq-ROFNs is proposed, and its properties are also probed. This distance measure is used in an improved weights determination method for decision-makers. A weighted projection optimization model is developed to evaluate the completely unknown attributes’ weights. The projection of assessment values is defined by the positive and negative ideal solutions, which determine the resemblance between two objects by considering their directional angle. An Indian cities’ ranking problem for a better solid waste management infrastructure is solved using the proposed approach based on composite indicators, like recycling waste, greenhouse gas emissions, waste generation, landfilling waste, recycling rate, waste-to-energy rate, and composting waste. Numerical comparisons, sensitivity analysis, and other relevant analyses are performed for validation.
Mathematics Subject Classification: 90C70
Key words: Interval-valued q-rung orthopair fuzzy number / COPRAS / multi-attribute group decision-making / projection method / solid waste management
© The authors. Published by EDP Sciences, ROADEF, SMAI 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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