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Handling of Synergy into an Algorithm for Project Portfolio Selection

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Recent Advances on Hybrid Intelligent Systems

Abstract

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.

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References

  1. Brans, J., Mareschal, B.: PROMETHEE Methods. In: Multiple Criteria Decision Analysis: State of the Art Surveys, pp. 163–190. Springer, New York (2005)

    Google Scholar 

  2. Castro, M.: Development and implementation of a framework for the forming of R & D portfolios in public organizations. Masters Thesis, Nuevo Leon Autonomous University (2007)

    Google Scholar 

  3. Carazo, A.F., Gómez, T., Molina, J., Hernández-Díaz, A.G., Guerreo, F.M., Caballero, R.: Solving a comprehensive model for multiobjective project portfolio selection. Computers & Operations Research 37(4), 630–639 (2010)

    Article  MathSciNet  MATH  Google Scholar 

  4. Coello, C., Van Veldhuizen, D.A.C.A., Lamont, G.B.: Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic Publishers, New York (2002)

    MATH  Google Scholar 

  5. Coello Coello, C.A., Lamont, G.B., Van Veldhuizen, D.A.: Evolutionary Algorithms for Solving Multi-Objective Problems. In: Genetic and Evolutionary Computation, 2nd edn. Springer (2007)

    Google Scholar 

  6. Doerner, K., Gutjahr, W.J., Hartl, R., Strauss, C., Stummer, C.: Pareto ant colony optimization: A metaheuristic approach to multiobjective portfolio selection. Annals OR 131, 79–99 (2004)

    Article  MathSciNet  MATH  Google Scholar 

  7. Dorigo, M., Gambardella, L.: Ant colony system: A cooperative learning approach to the traveling salesman problem. IEEE Transactions on Evolutionary Computation 1(1), 53–66 (1997)

    Article  Google Scholar 

  8. Doumpos, M., Marinakis, M., Marimaki, Y., Zopounidis, M.: An evolutionary approach to construction of outranking models for multicriteria classification: The case of ELECTRE TRI method. European Journal of Operational Research 199(2), 496–505 (2009)

    Article  MATH  Google Scholar 

  9. Durillo, J.J., Nebro, A.J., Coello Coello, C.A., García-Nieto, J., Luna, F., Alba, E.: A study of multiobjective metaheuristics when solving parameter scalable problems. IEEE Transactions on Evolutionary Computation 14(4), 618–635 (2010)

    Article  Google Scholar 

  10. Fernández, E., López, E., López, F., Coello Coello, C.A.: Increasing selective pressure towards the best compromise in evolutionary multiobjective optimization: The extended NOSGA method. Information Sciences 181(1), 44–56 (2011)

    Article  MathSciNet  MATH  Google Scholar 

  11. Fernández, E., López, E., Bernal, S., Coello Coello, C.A., Navarro, J.: Evolutionary multiobjective optimization using an outrankingbased dominance generalization. Computers & Operations Research 37(2), 390–395 (2010)

    Article  MATH  Google Scholar 

  12. Fernández, E., Navarro, J.: A genetic search for exploiting a fuzzy preference model of portfolio problems with public projects. Annals OR 117, 191–213 (2002)

    Article  MATH  Google Scholar 

  13. Fernández, E., Navarro, J., Bernal, S.: Multicriteria sorting using a valued indifference relation under a preference disaggregation paradigm. European Journal of Operational Research 198(2), 602–609 (2009)

    Article  MATH  Google Scholar 

  14. Fernández, E., Flerida, L., Mazcorro, G.: Multi-objective optimisation of an outranking model for public resources allocation on competing projects Int. J. Operational Research 5(2) (2009)

    Google Scholar 

  15. García, R.: Hyper-heuristic to solve the problem of social portfolio. Master’s Thesis, Madero Institute of Technology (2010)

    Google Scholar 

  16. Ghasemzadeh, F., Archer, N., Iyogun, P.: A zero-one model for project portfolio selection and scheduling. Journal of the Operational Research Society 50(7), 745–755 (1999)

    MATH  Google Scholar 

  17. Hakanan, J., Miettinen, K., Sahlstedt, K.: Simulation-based interactive multiobjective optimization in wastewater. In: International Conference on Engineering Optimization, ENGOPT 2008, Río de Janeiro (2008)

    Google Scholar 

  18. Liessio, J., Mild, P., Salo, A.: Preference programming for robust portfolio modeling and project selection. European Journal of Operation Research 181, 1488–1505 (2007)

    Article  Google Scholar 

  19. Marakas, G.: Decision Support Systems and Megaputer, 2nd edn. Prentice Hall, Upper Saddle River

    Google Scholar 

  20. Reiter, P.: Metaheuristic Algorithms for Solving Multiobjective/ Stochastic Scheduling and Routing Problems. Ph.D. Thesis. University of Wien (2010)

    Google Scholar 

  21. Roy, B.: The Outranking Approach and the Foundations of ELECTRE methods. In: Reading in Multiple Criteria Decision Aid, pp. 155–183. Spinger (1990)

    Google Scholar 

  22. Roy, B.: Multicriteria Methodology for Decision Aiding. Kluwer, Dordrecht (1996)

    MATH  Google Scholar 

  23. Zitzler, E., Thiele, L.: Multiobjective Evolutionary Algorithms: A comparative case study and the Strength Pareto Evolutionary Algorithm. IEEE Transactions on Evolutionary Computation 3(4), 257–271 (1999)

    Article  Google Scholar 

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Correspondence to Gilberto Rivera .

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Rivera, G., Gómez, C.G., Fernández, E.R., Cruz, L., Castillo, O., Bastiani, S.S. (2013). Handling of Synergy into an Algorithm for Project Portfolio Selection. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Recent Advances on Hybrid Intelligent Systems. Studies in Computational Intelligence, vol 451. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33021-6_33

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  • DOI: https://doi.org/10.1007/978-3-642-33021-6_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-33020-9

  • Online ISBN: 978-3-642-33021-6

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