<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>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 3<italic>σ</italic> 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.</p>
</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.

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

Northwest Sci-Tech University of Agriculture and Forestry

Applied Mathematics and Nonlinear Sciences

This work is licensed under the Creative Commons Attribution 4.0 International License.

Random multi-attribute decision-making is a finite option selection problem related to multiple attributes, and the attribute values are random variables. Its...

	u₁	u₂	u₃	u₄	u₅	u₆

s₁	2	2.5	[55,56]	[94,114]	Normal (0.4, 0.5, 0.6)	Very high (0.85, 0.9, 0.95, 1)
s₂	2.5	2.7	[30,40]	[84,104]	Low (0.2, 0.3, 0.4)	Normal (0.3, 0.4, 0.6, 0.7)
s₃	1.8	2.4	[50,60]	[100,120]	High (0.6, 0.7, 0.8)	High (0.5, 0.6, 0.8, 0.9)
s₄	2.2	2.6	[35,45]	[90,110]	Normal (0.4, 0.5, 0.6)	Normal (0.3, 0.4, 0.6, 0.7)

β	s1	s2	s3	s4

0	0.6726	0.0944	0.7366	0.3451
0.2	0.6705	0.0994	0.7358	0.3472
0.4	0.6683	0.1053	0.735	0.3496
0.6	0.666	0.1118	0.734	0.3522
0.8	0.6637	0.1191	0.7329	0.355
1	0.6613	0.1296	0.7316	0.358

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

Publié en ligne: 30 déc. 2021

Pages: 719 - 728

Reçu: 17 juin 2021

Accepté: 24 sept. 2021

DOI: https://doi.org/10.2478/amns.2021.2.00147

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

© 2021 Siqi Shen, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

The six attribute values of the four robots

β influence on the closeness of each plan

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

Publié en ligne: 30 déc. 2021

Pages: 719 - 728

Reçu: 17 juin 2021

Accepté: 24 sept. 2021

DOI: https://doi.org/10.2478/amns.2021.2.00147

Mots clésnormal random variables, mixed multi-attribute decision-making, entropy, subjective weight, objective weight, supply chain risk management

© 2021 Siqi Shen, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Fig. 1

Fig. 2

Fig. 3

The six attribute values of the four robots

β influence on the closeness of each plan

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