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Intelligent Techniques in Engineering Management pp 21–44Cite as

Possibilistic Models of Risk Management

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Part of the book series: Intelligent Systems Reference Library ((ISRL,volume 87))

Abstract

In the traditional treatment, risk situations are modeled by random variables. This chapter focuses on risk situations described by fuzzy numbers . The first goal of the chapter is to define and characterize possibilistic risk aversion and study some of its indicators. The second goal is the study of two possibilistic models of risk management : a coinsurance problem and an investment portfolio problem.

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Author information

Authors and Affiliations

  1. Department of Economic Cybernetics, Academy of Economic Studies, Piata Romana No 6, Oficiul Postal 22, R 70167, Bucharest, Romania

    Irina Georgescu

  2. Department of Business Administration, Romania and Loyola-ETEA University, C/Escritor Castilla Aguayo 4, 14004, Cordoba, Spain

    Irina Georgescu

  3. Institute for Advanced Management Systems Research, Åbo Akademi University, Jouhakaisenkatu 3-5 B 6th floor, 20520, Turku, Finland

    Jani Kinnunen

  4. Department of Business Administration, Loyola-ETEA University, C/Escritor Castilla Aguayo 4, 14004, Cordoba, Spain

    Ana Maria Lucia-Casademunt

Authors
  1. Irina Georgescu
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  2. Jani Kinnunen
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  3. Ana Maria Lucia-Casademunt
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Corresponding author

Correspondence to Irina Georgescu .

Editor information

Editors and Affiliations

  1. Department of Industrial Engineering Management Faculty, Istanbul Technical University, Istanbul, Turkey

    Cengiz Kahraman

  2. Department of Industrial Engineering, Istanbul Technical University Management Faculty, Istanbul, Turkey

    Sezi Çevik Onar

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Georgescu, I., Kinnunen, J., Lucia-Casademunt, A.M. (2015). Possibilistic Models of Risk Management. In: Kahraman, C., Çevik Onar, S. (eds) Intelligent Techniques in Engineering Management. Intelligent Systems Reference Library, vol 87. Springer, Cham. https://doi.org/10.1007/978-3-319-17906-3_2

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  • DOI: https://doi.org/10.1007/978-3-319-17906-3_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17905-6

  • Online ISBN: 978-3-319-17906-3

  • eBook Packages: EngineeringEngineering (R0)

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