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An Interval-Based Approach for Evolutionary Multi-Objective Optimization of Project Portfolios

Author

Listed:
  • Fausto Balderas

    (Postgraduate & Research Division, National Mexican Institute of Technology/Madero Institute of Technology, 89440, Tamaulipas, Mexico)

  • Eduardo Fernandez

    (#x2020;Faculty of Civil Engineering, Autonomous University of Sinaloa, 80040, Sinaloa, Mexico)

  • Claudia Gomez-Santillan

    (Postgraduate & Research Division, National Mexican Institute of Technology/Madero Institute of Technology, 89440, Tamaulipas, Mexico)

  • Nelson Rangel-Valdez

    (#x2021;CONACYT-Research Fellow, National Mexican Institute of Technology/Madero Institute of Technology, 89440, Tamaulipas, Mexico)

  • Laura Cruz

    (Postgraduate & Research Division, National Mexican Institute of Technology/Madero Institute of Technology, 89440, Tamaulipas, Mexico)

Abstract

Project portfolio selection is addressed here as a multi-objective optimization problem. This work introduces an interval-based method that takes into consideration imperfect knowledge of the contribution of projects to a portfolio, the project requirements, available resources and preference parameters in the model. The multi-objective optimization problem is solved using an evolutionary algorithm that is adapted to handle intervals. To direct the search toward the region of interest of the Pareto frontier, the preferences of the decision maker (DM) are incorporated using an interval-based outranking approach. This allows to address problems with many objective functions; intransitive preferences and incomparability situations can also be handled using this approach. In terms of analyzing robustness, the DM can obtain different solutions according to his/her level of conservatism. The effectiveness of this proposal was tested both on an example from the related literature and another example of a public project portfolio with nine objective functions and large number of applicant projects.

Suggested Citation

  • Fausto Balderas & Eduardo Fernandez & Claudia Gomez-Santillan & Nelson Rangel-Valdez & Laura Cruz, 2019. "An Interval-Based Approach for Evolutionary Multi-Objective Optimization of Project Portfolios," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1317-1358, July.
    • Handle: RePEc:wsi:ijitdm:v:18:y:2019:i:04:n:s021962201950024x
    DOI: 10.1142/S021962201950024X
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    References listed on IDEAS

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    2. Liesiö, Juuso & Mild, Pekka & Salo, Ahti, 2008. "Robust portfolio modeling with incomplete cost information and project interdependencies," European Journal of Operational Research, Elsevier, vol. 190(3), pages 679-695, November.
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    Cited by:

    1. Fernández, Eduardo & Navarro, Jorge & Solares, Efrain, 2022. "A hierarchical interval outranking approach with interacting criteria," European Journal of Operational Research, Elsevier, vol. 298(1), pages 293-307.
    2. Balderas, Fausto & Fernández, Eduardo & Cruz-Reyes, Laura & Gómez-Santillán, Claudia & Rangel-Valdez, Nelson, 2022. "Solving group multi-objective optimization problems by optimizing consensus through multi-criteria ordinal classification," European Journal of Operational Research, Elsevier, vol. 297(3), pages 1014-1029.
    3. Fernández, Eduardo & Figueira, José Rui & Navarro, Jorge & Solares, Efrain, 2022. "Handling imperfect information in multiple criteria decision-making through a comprehensive interval outranking approach," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
    4. Gulnaz Raffiq & Iram Sajjad Dar & Muhammad Ahsan Ul Haq & Eduardo Ramos, 2022. "The Marshall–Olkin Inverted Nadarajah–Haghighi Distribution: Estimation and Applications," Annals of Data Science, Springer, vol. 9(6), pages 1323-1338, December.
    5. Eduardo Fernández & Claudia Gómez-Santillán & Nelson Rangel-Valdez & Laura Cruz-Reyes, 2022. "Group Multi-Objective Optimization Under Imprecision and Uncertainty Using a Novel Interval Outranking Approach," Group Decision and Negotiation, Springer, vol. 31(5), pages 945-994, October.

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