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Genetic algorithm-based multi-criteria project portfolio selection

  • Lean Yu
  • , Shouyang Wang
  • , Fenghua Wen
  • , Kin Keung Lai

    Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review

    Abstract

    Project portfolio selection is one of the most important decision-making problems for most organizations in project management and engineering management. Usually project portfolio decisions are very complicated when project interactions in terms of multiple selection criteria and preference information of decision makers (DMs) in terms of the criteria importance are taken into consideration simultaneously. In order to solve this complex decision-making problem, a multi-criteria project portfolio selection problem considering project interactions in terms of multiple selection criteria and DMs' preferences is first formulated. Then a genetic algorithm (GA)-based nonlinear integer programming (NIP) approach is used to solve the multi-criteria project portfolio selection problem. Finally, two illustrative examples are presented for demonstration and verification purposes. Experimental results obtained indicate that the GA-based NIP approach can be used as a feasible and effective solution to multi-criteria project portfolio selection problems. © 2010 Springer Science+Business Media, LLC.
    Original languageEnglish
    Pages (from-to)71-86
    JournalAnnals of Operations Research
    Volume197
    Issue number1
    DOIs
    Publication statusPublished - 2012

    Research Keywords

    • Genetic algorithm
    • Multi-criteria decision making
    • Nonlinear integer programming
    • Preference
    • Project interactions
    • Project portfolio selection

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