Induced generalized ordered weighted logarithmic aggregation operators
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Alfaro García, Víctor
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Induced generalized ordered weighted logarithmic aggregation operators
Abstract
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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2016 IEEE Symposium Series on Computational Intelligence, SSCI 20169 February 2017, Article number 7850012
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