Premium
Determination of the Attitudinal Character by Self‐Evaluation for the Maximum Entropy OWA Approach
Author(s) -
Ma FengMei,
Guo YaJun
Publication year - 2013
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/int.21618
Subject(s) - character (mathematics) , entropy (arrow of time) , computer science , rank (graph theory) , principle of maximum entropy , artificial intelligence , set (abstract data type) , value (mathematics) , mathematical optimization , mathematics , machine learning , combinatorics , physics , geometry , quantum mechanics , programming language
The attitudinal character plays an important role in the maximum entropy ordered weighted averaging (MEOWA) approach. We propose a self‐evaluation model to determine the attitudinal character for each alternative in multicriteria decision making with MEOWA operators. The value of the attitudinal character determined for each alternative by self‐evaluation may be different; and each alternative can reach its highest rank with MEOWA weights, when the attitudinal character is determined for it. Then, to obtain an overall set of MEOWA weights by different attitudinal character values, the preemptive goal programming (PGP) model proposed by Wang can be used. Finally, the evaluation process of the service quality for five online stores is given to illustrate the application of the proposed method.