期刊
KNOWLEDGE-BASED SYSTEMS
卷 36, 期 -, 页码 268-279出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2012.07.006
关键词
Group decision making; Aggregation operator; OWA operator; Generalized logarithmic proportional averaging operator; Generalized logarithm chi-square method
资金
- National Natural Science Foundation of China [71071002]
- Provincial Natural Science Research Project of Anhui Colleges [KJ2012A026]
- Academic Innovation Team of Anhui University [KJTD001B, SKTD007B]
- Foundation for the Young Scholar of Anhui University [2009QN022B]
In this paper, we present a new operator called the generalized ordered weighted logarithmic proportional averaging (GOWLPA) operator based on an optimal model, which is an extension of the generalized ordered weighted logarithm averaging (GOWLA) operator. The key advantage of the GOWLPA operator is not only that it is an aggregation operator with theoretic basis on aggregation, but also that the weighting vector of the GOWLPA operator depends on the input arguments. We analyze some properties and families of the GOWLPA operator and further develop generalizations of this operator including the generalized hybrid logarithmic proportional averaging (GHLPA) operator and the quasi ordered weighted logarithmic proportional averaging (QOWLPA) operator. To determine the GOWLPA operator weights, we propose the generalized logarithm chi-square method (GLCSM) which does not follow a regular distribution. Finally, we give a numerical example of an investment selection to illustrate the application of the GOWLPA operator to multiple attribute group decision making. (C) 2012 Elsevier B.V. All rights reserved.
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