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Fuzzy Multi-attribute Evaluation of Investments

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Advances in ICT for Business, Industry and Public Sector

Part of the book series: Studies in Computational Intelligence ((SCI,volume 579))

Abstract

Most companies have a large number of projects that they would like to accomplish for various reasons. However, financial and material limitations cause that only some of the investments can be undertaken, which rises the problem of selecting the portfolio of the most effective investment projects. Selecting a portfolio from available project proposals is crucial for the success of each company. This paper proposes a practical framework for modelling projects portfolio selection problem with fuzzy parameters resulting from uncertainty associated with decision makers’ judgment. A fuzzy multi-attribute decision-making approach is adopted. A two-step evaluation model that combines fuzzy AHP and fuzzy TOPSIS methods is used to rank potential projects. The proposed approach is illustrated by an empirical study of a real case from steel industry involving fifteen criteria and ten projects. The case study shows the effectiveness and feasibility of the proposed evaluation procedure.

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Authors and Affiliations

  1. AGH University of Science and Technology, Kraków, Poland

    Bogdan Rȩbiasz, Bartłomiej Gaweł & Iwona Skalna

Authors
  1. Bogdan Rȩbiasz
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  2. Bartłomiej Gaweł
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  3. Iwona Skalna
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Corresponding author

Correspondence to Bartłomiej Gaweł .

Editor information

Editors and Affiliations

  1. Katowice University of Economics, Katowice, Poland

    Maria Mach-Król

  2. Katowice University of Economics, Katowice, Poland

    Celina M. Olszak

  3. AGH University of Mining and Metallurgy, Kraków, Poland

    Tomasz Pełech-Pilichowski

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Rȩbiasz, B., Gaweł, B., Skalna, I. (2015). Fuzzy Multi-attribute Evaluation of Investments. In: Mach-Król, M., M. Olszak, C., Pełech-Pilichowski, T. (eds) Advances in ICT for Business, Industry and Public Sector. Studies in Computational Intelligence, vol 579. Springer, Cham. https://doi.org/10.1007/978-3-319-11328-9_9

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  • DOI: https://doi.org/10.1007/978-3-319-11328-9_9

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11327-2

  • Online ISBN: 978-3-319-11328-9

  • eBook Packages: EngineeringEngineering (R0)

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