A Public-Participation-Based Mixed Multiattribute Decision-Making Approach for Major Public Affairs. (9th August 2021)

• Record Type: Journal Article
• Authors: Cai, Chenguang; Luo, Yong; Zhu, Guiju; Zou, Hao
• Other Names: Rak Ewa Academic Editor.
• Is Part Of: Mathematical problems in engineering. Volume 2021(2021)
• Publication Date: 2021-08-09
• Subjects: Engineering mathematics -- Periodicals; 510.2462
• DOI: 10.1155/2021/7550055
• Languages: English
• ISSNs: 1024-123X

Abstract

Abstract : The decision-making activities of major public affairs are closely related to the public, so the decision results of such affairs must be supported by the public. The public must participate in decision-making activities to ensure their effectiveness, which further increases the complexity. In addition, attribute information and public opinion usually present different forms of expression in this type of problem, making decision-making more difficult. Therefore, a suitable decision approach must be chosen to deal with this type of decision problem. This paper addresses the decision-making characteristics of major public affairs and proposes a public-participation-based decision-making approach for mixed multiattribute decision-making problems in major public affairs. The proposed approach can work with entirely unknown attribute weights and decision-making values represented in multiple formats. First, the statistical distribution of public opinions is determined based on the expectation of the attributes, resulting in decision-making reference points for various attributes. The different forms of attributes and reference points are unified. Then, the values of the attributes and reference points are standardized. Afterward, the attribute prospect value for each alternative is calculated using the attribute value and corresponding reference points. The attribute weight intervals are determined based on the importance information of the attributes provided by the public. An optimization model is established to determine the attribute weights to maximize the alternative attribute deviation. Next, the comprehensive prospect value of each alternative is obtained to determine the ranking of the alternatives. Finally, a case analysis is conducted with a method comparison and sensitivity analysis, and the feasibility and effectiveness of the proposed approach are verified. In the proposed method, the reference points for each attribute are set according to the distribution characteristics and ambiguity of public expectations, guaranteeing that public expectations can be effectively reflected in the attribute reference points. In the process of attribute weighting, based on the information for the attribute importance given by the public, the range of attribute weights is determined. Then, we obtain the exact value of the attribute weights using an optimization model to maximize the alternative attribute deviation. The final result of the attribute weights ensures the full expression of public opinion and can improve the differentiation of decision results, which is convenient for ranking alternatives. During evaluation of the alternatives based on prospect theory, the expression forms of attributes and reference points are unified. Subsequently, the values of them are normalized, which satisfy the decision-making requirement of major public affairs.