@article{Attaullah2023, 
author = { Attaullah and Asghar Khan and Noor Rehman and Fuad S. Al-Duais and Afrah Al-Bossly and Laila A. Al-Essa and Elsayed M Tag-eldin},
title = {A novel decision model with Einstein aggregation approach for garbage disposal plant site selection under    q-rung orthopair hesitant fuzzy rough information},
year = {2023},
journal = {AIMS Mathematics},
volume = {8},
number = {10},
pages = {22830-22874},
keywords = {the q-rung orthopair hesitant fuzzy rough sets, Einstein aggregation operators, Garbage disposal site selection, decision making, sensitivity analysis},
url = {https://www.sciopen.com/article/10.3934/math.20231163},
doi = {10.3934/math.20231163},
abstract = {Environmental science and pollution research has benefits around the globe. Human activity produces more garbage throughout the day as the world's population and lifestyles rise. Choosing a garbage disposal site (GDS) is crucial to effective disposal. In illuminated of the advancements in society, decision-makers concede a significant challenge for assessing an appropriate location for a garbage disposal site. This research used a multi-attribute decision-making (MADM) approach based on    q-rung orthopair hesitant fuzzy rough (   q-ROHFR) Einstein aggregation information for evaluating GDS selection schemes and providing decision-making (DM) support to select a suitable waste disposal site. In this study, first, q-ROHFR Einstein average aggregation operators are integrated. Some intriguing characteristics of the suggested operators, such as monotonicity, idempotence and boundedness were also explored. Then, a MADM technique was established using the novel concept of    q-ROHFR aggregation operators under Einstein t-norm and t-conorm. In order to help the decision makers (DMs) make a final choice, this technique aims to rank and choose an alternative from a collection of feasible alternatives, as well as to propose a solution based on the ranking of alternatives for a problem with conflicting criteria. The model's adaptability and validity are then demonstrated by an analysis and solution of a numerical issue involving garbage disposal plant site selection. We performed a the sensitivity analysis of the proposed aggregation operators to determine the outcomes of the decision-making procedure. To highlight the potential of our new method, we performed a comparison study using the novel extended TOPSIS and VIKOR schemes based on    q-ROHFR information. Furthermore, we compared the results with those existing in the literature. The findings demonstrate that this methodology has a larger range of information representation, more flexibility in the assessment environment, and improved consistency in evaluation results.}
}