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The Strategic Weight Manipulation Model in Uncertain Environment: A Robust Risk Optimization Approach

Authors :
Shaojian Qu
Lun Wang
Ying Ji
Lulu Zuo
Zheng Wang
Source :
Systems, Vol 11, Iss 3, p 151 (2023)
Publication Year :
2023
Publisher :
MDPI AG, 2023.

Abstract

Due to the complexity and uncertainty of decision-making circumstances, it is difficult to provide an accurate compensation cost in strategic weight manipulation, making the compensation cost uncertain. Simultaneously, the change in the attribute weight is also accompanied by risk, which brings a greater challenge to manipulators’ decision making. However, few studies have investigated the risk aversion behavior of manipulators in uncertain circumstances. To address this research gap, a robust risk strategic weight manipulation approach is proposed in this paper. Firstly, mean-variance theory (MVT) was used to characterize manipulators’ risk preference behavior, and a risk strategic weight manipulation model was constructed. Secondly, the novel robust risk strategic weight manipulation model was developed based on the uncertainty caused by the estimation error of the mean and covariance matrix of the unit compensation cost. Finally, a case of emergency facility location was studied to verify the feasibility and effectiveness of the proposed method. The results of the sensitivity analysis and comparative analysis show that the proposed method can more accurately reflect manipulators’ risk preference behavior than the deterministic model. Meanwhile, some interesting conclusions are revealed.

Details

Language :
English
ISSN :
11030151 and 20798954
Volume :
11
Issue :
3
Database :
Directory of Open Access Journals
Journal :
Systems
Publication Type :
Academic Journal
Accession number :
edsdoj.2cddbdad6e50426ab7a96ca0e4d704a8
Document Type :
article
Full Text :
https://doi.org/10.3390/systems11030151