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Two novel methodologies for considering aggregation functions by implicit equations and minimization problems
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DOI：10.1016/j.ejor.2018.04.023.png)
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In this work, we consider the problem of defining aggregation functions by means of two distinct methodologies. In the first one, we obtain an aggregation function in an implicit way, from a function which fulfills appropriate conditions. The second methodology, related to the idea of penalty function, is based on the minimization of a distance or error and can be seen as a generalization of the idea of correlation in statistics. We analyze the aggregation functions obtained with both methodologies and we present an illustrative decision-making example to show their different behaviors. (C) 2018 Elsevier B.V. All rights reserved.
Keyword:
Fuzzy sets
Aggregation function
Minimization problem
Least squares method
Implicit equation
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6
论文数:
2.2W
被引数:
6.4W
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