Induced generalized ordered weighted logarithmic aggregation operators

Publication Type:
Conference Proceeding
Citation:
2016 IEEE Symposium Series on Computational Intelligence, SSCI 2016, 2017
Issue Date:
2017-02-09
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© 2016 IEEE. We present the induced generalized ordered weighted logarithmic aggregation (IGOWLA) operator. It is an extension of the generalized ordered weighted logarithmic aggregation (GOWLA) operator. The IGOWLA operator uses order-induced variables that modify the reordering mechanism of the arguments to be aggregated. The main advantage of the induced process is the consideration of the complex attitude of the decision makers. We study some properties of the IGOWLA operator, such as idempotency, commutativity, boundedness and monotonicity. Finally we present an illustrative example of a group decision-making procedure using a multi-person analysis and the IGOWLA operator in the area of innovation management.
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