Risk Management Using Fuzzy Logic and Genetic Algorithms

Teresa C. Rubinson () and Georgette Geotsi ()
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Teresa C. Rubinson: TCR, Inc.
Georgette Geotsi: Sacred Heart University

A chapter in The Ordered Weighted Averaging Operators, 1997, pp 155-166 from Springer

Abstract: Abstract Risk management is a complex and subjective task. It involves identifying risk factors, setting risk thresholds, and determining appropriate actions to reduce risk [Bernstein, 1995]. Fuzzy logic techniques are especially well suited to subjective problems of this type. Traditionally, fuzzy techniques have relied on user supplied data to define fuzzy functional parameters. However, in real life people are notoriously inaccurate and unreliable in reporting their preferences, especially as the complexity and uncertainty of the problem increases. In this paper, we describe a methodology which uses a genetic algorithm to automate and validate derivation of fuzzy functional parameters.

Keywords: Risk management; fuzzy logic; genetic algorithms; Ordered Weighted Averaging (OWA) Operators; fuzzy multiple criteria decision making; fuzzy ranking (search for similar items in EconPapers)
Date: 1997
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4615-6123-1_13

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DOI: 10.1007/978-1-4615-6123-1_13

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