Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 6, Issue 2


Published
on

December 13, 2021


Pages

373-382


DOI

Article

Application of multi-attribute decision-making methods based on normal random variables in supply chain risk management

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Authors

Liye Zhang Affiliation:
School of Finance and Accounting, Henan University of Animal Husbandry and Economy, Zhengzhou, Henan 450000, China
, Adil Omar Khadidos Affiliation:
Department of Information Technology, Faculty of Computing and Information Technology, King Abdulaziz University, Jeddah, Saudi Arabia
and Radwan Kharabsheh Affiliation:
Applied Science University, Al Eker, Kingdom of Bahrain


Abstract

For the multi-criteria group decision-making problem where the criterion value is a normal interval number and the weight information is incomplete, the normal interval number and its compromise expected value, compromise mean square error, algorithm, weighted arithmetic average of normal interval number (ININWAA) Operator, the ordered weighted average (ININOWA) operator of normal interval numbers and the mixed weighted average (ININHA) operator of normal interval numbers, and a multi-criteria group with incomplete information based on normal interval numbers is proposed. Decision-making methods. This method uses ININWAA operator and INNHA operator to integrate criterion values, uses the compromise mean square error of criterion values, establishes an optimisation model to solve the optimal criterion weights and uses the expectation variance criterion to determine the order of the schemes. The case analysis shows the effectiveness and feasibility of this method.


Keywords

group decision making, normal interval number, ensemble operator, 34A34


Citation

Zhang, L., Khadidos, A. O., & Kharabsheh, R. (2021). Application of multi-attribute decision-making methods based on normal random variables in supply chain risk management. Applied Mathematics and Nonlinear Sciences, 6(2), 373–382. https://doi.org/10.2478/amns.2021.2.00061

Published by: Engineering Journals

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