Handling of Synergy into an Algorithm for Project Portfolio Selection

  • Gilberto RiveraEmail author
  • Claudia G. Gómez
  • Eduardo R. Fernández
  • Laura Cruz
  • Oscar Castillo
  • Samantha S. Bastiani
Part of the Studies in Computational Intelligence book series (SCI, volume 451)


Public and private organizations continuously invest on projects. With a number of candidate projects bigger than those ones that can be funded, the organization faces the problem of selecting a portfolio of projects that maximizes the expected benefits. The selection is made on the evaluation of project groups and not on the evaluation of single projects. However, there is a factor that must be taken account, since it can significantly change the evaluation of groups: synergy. This is that two or more projects are complemented in a way that generates an additional benefit to they already own individually. Redundancy, a special case of synergy, occurs when two or more projects cannot be financed simultaneously. Both features add complexity to the evaluation of project groups. This article presents an evaluation of the two most used alternatives for handling synergy, in order to incorporate it into an ant-colony metaheuristic for solving project portfolio selection.


Pareto Front Portfolio Selection Preference Model Pareto Frontier Project Portfolio 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gilberto Rivera
    • 1
    Email author
  • Claudia G. Gómez
    • 1
  • Eduardo R. Fernández
    • 2
  • Laura Cruz
    • 1
  • Oscar Castillo
    • 3
  • Samantha S. Bastiani
    • 1
  1. 1.Madero Institute of TechnologyMaderoMéxico
  2. 2.Sinaloa Autonomous UniversitySinaloaMéxico
  3. 3.Tijuana Institute of TechnologyTijuanaMéxico

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