Applied Mathematics and Nonlinear Sciences
Journal license

Journal

Applied Mathematics and Nonlinear Sciences


Volume
& Issue

Volume 6, Issue 2


Published
on

December 30, 2021


Pages

719-728


DOI

Article

Multi-attribute decision-making methods based on normal random variables in supply chain risk management

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Authors

Siqi Shen Affiliation:
Northwest Sci-Tech University of Agriculture and Forestry, Shanxi, 712100, China


Abstract

Random multi-attribute decision-making is a finite option selection problem related to multiple attributes, and the attribute values are random variables. Its application and supply chain risk management can transform interval decision numbers and fuzzy decision numbers into standardised decisions. Based on this research background, the article provides a primary method to determine the randomness of standard random variables based on expectations and variance through theoretical analysis. Second, the article determines the range of the total utility value of each supply chain selection plan based on the 3σ principle. Experiments have proved that this method can solve unifying opinions due to different knowledge, experience, and preferences of evaluation experts. This provides a new method of supplier selection.


Keywords

normal random variables, mixed multi-attribute decision-making, entropy, subjective weight, objective weight, supply chain risk management, 90B50


Citation

Shen, S. (2021). Multi-attribute decision-making methods based on normal random variables in supply chain risk management. Applied Mathematics and Nonlinear Sciences, 6(2), 719–728. https://doi.org/10.2478/amns.2021.2.00147

Published by: Engineering Journals

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