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Nonadditive Multiattribute Utility Functions for Portfolio Decision Analysis

Author

Listed:
  • Juuso Liesiö

    (Department of Information and Service Management, Aalto University School of Business, 00076 Aalto, Finland)

  • Eeva Vilkkumaa

    (Department of Information and Service Management, Aalto University School of Business, 00076 Aalto, Finland)

Abstract

Portfolio decision analysis models support selecting a portfolio of projects in view of multiple objectives and limited resources. In applications, portfolio utility is commonly modeled as the sum of the projects’ multiattribute utilities, although such approaches lack rigorous decision-theoretic justification. This paper establishes the axiomatic foundations of a more general class of multilinear portfolio utility functions, which includes additive and multiplicative portfolio utility functions as special cases. Furthermore, we develop preference elicitation techniques to assess these portfolio utility functions as well as optimization models to identify the most preferred portfolio in view of resource and other constraints. We also examine how the functional form of the portfolio utility function affects decision recommendations by using randomly generated and real problem instances.

Suggested Citation

  • Juuso Liesiö & Eeva Vilkkumaa, 2021. "Nonadditive Multiattribute Utility Functions for Portfolio Decision Analysis," Operations Research, INFORMS, vol. 69(6), pages 1886-1908, November.
    • Handle: RePEc:inm:oropre:v:69:y:2021:i:6:p:1886-1908
    DOI: 10.1287/opre.2020.2046
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    References listed on IDEAS

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    Cited by:

    1. Mendy Tönsfeuerborn & Rüdiger von Nitzsch & Johannes Ulrich Siebert, 2026. "Linear Transformation of One-Dimensional Utility Functions: Empirical Study on the Impact on the Final Ranking of Alternatives in Personal Decisions," Decision Analysis, INFORMS, vol. 23(1), pages 46-64, March.
    2. Wu, Qiong & Wang, Wei & Zhang, Sainan & Xu, Huifu, 2025. "Bi-attribute utility preference robust optimization: A continuous piecewise linear approximation approach," European Journal of Operational Research, Elsevier, vol. 323(1), pages 170-191.
    3. Pekka Korhonen & Juuso Liesiö & Aapo Siljamäki & Jyrki Wallenius, 2025. "Supporting Scenario‐Based Decision‐Making With Multi‐Objective Optimization," Futures & Foresight Science, John Wiley & Sons, vol. 7(2), August.

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