Supplier Selection Based on Supplier Portrait and Markov Monte Carlo Method

Authors

Bingli Sun, 1. School of Automation Science & Electrical Engineering, Beihang University, Beijing 100191, China;;
Song Xiao, 2. School of Cyber Science & Technology, Beihang University, Beijing 100191, China;
Guanghong Gong, 1. School of Automation Science & Electrical Engineering, Beihang University, Beijing 100191, China;;

Abstract

Abstract: The supplier selection problem is a complex multi-objective decision-making problem and the key is how to establish the supplier's portrait. For the supplier selection of aerospace equipment, enterprise qualification management, business risks, and product quality are comprehensively considered. Based on Bayesian theory, the multi-parameter joint distribution derivation of portrait sample data is realized. Combined with the mathematical model derived, a Markov Monte Carlo simulation method is proposed. And combined with Gibbs sampler, the supplier ranking and selection are achieved when data is difficult to obtain or missing, which provides a new idea for supplier selection in the aerospace field.

Recommended Citation

Sun, Bingli; Xiao, Song; and Gong, Guanghong (2021) "Supplier Selection Based on Supplier Portrait and Markov Monte Carlo Method," Journal of System Simulation: Vol. 33: Iss. 11, Article 21.
DOI: 10.16182/j.issn1004731x.joss.21-FZ0664E
Available at: https://dc-china-simulation.researchcommons.org/journal/vol33/iss11/21

First Page

2720

Revised Date

2021-07-13

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.21-FZ0664E

Last Page

2732

CLC

TP391.9

Recommended Citation

Sun Bingli, Song Xiao, Gong Guanghong. Supplier Selection Based on Supplier Portrait and Markov Monte Carlo Method[J]. Journal of System Simulation, 2021, 33(11): 2720-2732.

Corresponding Author

Song Xiao,

DOI

10.16182/j.issn1004731x.joss.21-FZ0664E