Open Access

ARTICLE

Dynamic Multi-Attribute Decision-Making Method with Double Reference Points and Its Application

by Haoran Huang¹, Qinyong Lin², Weitong Chen³, Kai Fang⁴, Huazhou Chen⁵, Ken Cai^2,*

1 College of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China
2 College of Automation, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China
3 School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia
4 College of Economy and Trade, Zhongkai University of Agriculture and Engineering, Guangzhou, 510225, China
5 College of Science, Guilin University of Technology, Guilin, 541004, China

* Corresponding Author: Ken Cai. Email:

Computers, Materials & Continua 2021, 68(1), 1303-1320. https://doi.org/10.32604/cmc.2021.016163

Received 25 December 2020; Accepted 10 February 2021; Issue published 22 March 2021

Abstract

To better reflect the psychological behavior characteristics of loss aversion, this paper builds a double reference point decision making method for dynamic multi-attribute decision-making (DMADM) problem, taking bottom-line and target as reference pints. First, the gain/loss function is given, and the state is divided according to the relationship between the gain/loss value and the reference point. Second, the attitude function is constructed based on the results of state division to establish the utility function. Third, the comprehensive utility value is calculated as the basis for alternatives classification and ranking. Finally, the new method is used to evaluate the development level of smart cities. The results show that the new method can judge the degree to which the alternatives meet the requirements of the decision-maker. While the new method can effectively screen out the unsatisfactory alternatives, the ranking results of other alternatives are consistent with those of traditional methods.

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Citations