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A Decision Support System Framework for Public Project Portfolio Selection with Argumentation Theory

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Part of the book series: Studies in Computational Intelligence ((SCI,volume 547))

Abstract

In this chapter, we propose a framework for a Decision Support System (DSS) to aid in the selection of public project portfolios. Organizations are investing continuously and simultaneously in projects, however, they face the problem of having more projects than resources to implement them. Public projects are designed to favor society. Researches have commonly addressed the public portfolio selection problem with multicriteria algorithms, due to its high dimensionality. These algorithms focus on identifying a set of solutions in the Pareto frontier. However, the selection of the solution depends on the changing criteria of the decision maker (DM). A framework to support the DM is presented; it is designed to help the DM by a dialogue game to select the best portfolio in an interactive way. The framework is based on the argumentation theory and a friendly user interface. The dialogue game allows the DM to ask for justification on the project portfolio selection.

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References

  1. Fernández-González, E., Vega-López, I., Navarro-Castillo, J.: Public portfolio selection combining genetic algorithms and mathematical decision analysis. In: Bio-Inspired Computational Algorithms and Their Applications, pp. 139–160, INTECH (2012)

    Google Scholar 

  2. Godden, D.J., Walton, D.: Advances in the theory of argumentation schemes and critical questions. Informal Logic 27(3), 267–292 (2007)

    Google Scholar 

  3. Gordon, T. F., Walton, D.: The Carneades argumentation framework–using presumptions and exceptions to model critical questions. In: 6th Computational Models of Natural Argument Workshop (CMNA), European Conference on Artificial Intelligence (ECAI), Italy, pp. 5–13 (2006)

    Google Scholar 

  4. Karacapilidis, N., Papadias, D.: A computational approach for argumentative discourse in multi-agent decision making environments. AI Commun. 11(1), 21–33 (1997)

    Google Scholar 

  5. Labreuche, C., Maudet, N., Ouerdane, W.: Minimal and complete explanations for critical multi-attribute decisions. In: Algorithmic Decision Theory, pp. 121–134. Springer, Heidelberg (2011)

    Google Scholar 

  6. Mousseau, V., Stewart, T.: Progressive methods in multiple criteria decision analysis. PhD Thesis, Université Du Luxemburg (2007)

    Google Scholar 

  7. Ouerdane, W.: Multiple criteria decision aiding: a dialectical perspective. PhD Thesis, Université Paris Dauphine, Paris (2009)

    Google Scholar 

  8. Ouerdane, W., Dimopoulos, Y., Liapis, K., Moraitis, P.: Towards automating decision aiding through argumentation. J. Multi-Criteria Decis. Anal. 18(5–6), 289–309 (2011)

    Article  Google Scholar 

  9. Ouerdane, W., Maudet, N., Tsoukiàs, A.: Argument schemes and critical questions for decision aiding process. In: Proceedings of the 2nd International Conference on Computational Models of Argument (COMMA’08), pp. 285–296 (2008)

    Google Scholar 

  10. Ouerdane, W., Maudet, N., Tsoukias, A.: Argumentation theory and decision aiding. In: Trends in Multiple Criteria Decision Analysis, pp. 177–208. Springer, US (2010)

    Google Scholar 

  11. Reed, C., Rowe, G.: Araucaria: Software for argument analysis, diagramming and representation. Int. J. Artif. Intell. Tools 13(04), 961–979 (2004)

    Article  Google Scholar 

  12. Reed, C., Walton, D., Macagno, F.: Argument diagramming in logic, law and artificial intelligence. The Knowledge Engineering Review 22(01), 87–109 (2007)

    Article  Google Scholar 

  13. Visser, W., Hindriks, K.V., Jonker, C.M.: An argumentation framework for qualitative multi-criteria preferences. In: Theory and Applications of Formal Argumentation, pp. 85–98. Springer, Heidelberg (2012)

    Google Scholar 

  14. Walton, D., Gordon, T.F.: Critical questions in computational models of legal argument. Argumentation Artif. Intell. Law, 103–111 (2005)

    Google Scholar 

  15. Weistroffer, H.R., Smith, C.H.: Decision support for portfolio problems. Southern Association of Information Systems (SAIS), Savannah, Georgia (2005)

    Google Scholar 

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Acknowledgments

This work was partially financed by CONACYT, PROMEP and DGEST.

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Correspondence to Laura Cruz-Reyes .

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© 2014 Springer International Publishing Switzerland

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Cruz-Reyes, L., Medina Trejo, C., López Irrarragorri, F., Gómez Santillán, C.G. (2014). A Decision Support System Framework for Public Project Portfolio Selection with Argumentation Theory. In: Castillo, O., Melin, P., Pedrycz, W., Kacprzyk, J. (eds) Recent Advances on Hybrid Approaches for Designing Intelligent Systems. Studies in Computational Intelligence, vol 547. Springer, Cham. https://doi.org/10.1007/978-3-319-05170-3_32

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  • DOI: https://doi.org/10.1007/978-3-319-05170-3_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-05169-7

  • Online ISBN: 978-3-319-05170-3

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