The key issue of multi-attribute decision making is to determine the reasonable weights of the attributes. Considering the different advantages of the subjective weighting methods and the objective weighting methods, focus is put on studying the combination of Subjective-Objective weighting and its rationality. Firstly, according to the information conveyed by the attribute weights, a method is put forward to decompose the attribute weight information into the "ordered information" and "intensity information",The "ordered information" and "intensity information" of Subjective-Objective weights are then compared and analyzed.Furthermore, the principle of combined weights on balancing "ordered information" and "intensity information" which laid the foundation for an optimization model of the combination weighting is put forward. Secondly, an optimization model of the combined weighting method is established to find the Subjective-Objective weighting. The objective function is to minimize the deviation between the combination weight and the objective weight, the constraint is to minimize the deviation of the sequence between the combined weight and the subjective weight which balance the "ordered information" and "intensity information" of the attribute weight. Finally, the validity and the interpretability of the model is verified by an example and the feasibility of the combined weighting method is verified by an example of efficiency evaluation in a bank. Based on the decomposition of subjective and objective weight information, a combination weighting model, which balances "ordered information" and "intensity information" from a single attribute level is established. The combination is more flexible and ensures the compatibility and interpretability. It provides new ideas and references for the empowerment of multi-attribute decision-making.
LI Gang, LI Jian-ping, SUN Xiao-lei, WU Deng-sheng
. Research on a Combined Method of Subjective-Objective Weighting Based on the Ordered Information and Intensity Information[J]. Chinese Journal of Management Science, 2017
, 25(12)
: 179
-187
.
DOI: 10.16381/j.cnki.issn1003-207x.2017.12.019
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