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Quality-Assessment Model for Portfolios of Projects Expressed by a Priority Ranking

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Recent Advances on Hybrid Approaches for Designing Intelligent Systems

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

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Abstract

Organizations need to make decisions about how to invest and manage the resources to get more benefits, but, commonly the organization’s resources are not enough to support all project proposals. Thus, the decision maker (DM) wants to select the portfolio with the highest contribution to the organizational objectives. But in many practical cases, to know exactly the benefits associated to implement each proposal is too difficult, therefore it is questionable the issue of evaluating portfolio quality in these conditions In order to face these uncertainty situations, the DM usually ranks the applicant projects according to his/her preferences about an estimated impact of each portfolio. However, a correct modeling of the quality of the portfolio is indispensable to develop a model of coherent optimization to the ranking given by the DM. In the literature, this type of problems has been scantily approached in spite of being present in many practical situations of assignment of resources. In this Chapter we propose a quality model of portfolio and an algorithm that solves it. The experimental results show that the algorithm that includes our model offers benefits to the decision maker, and his advantages highlighted with respect to the related works reported in the state of the art.

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Correspondence to Claudia Gómez .

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Samantha Bastiani, S., Cruz-Reyes, L., Fernandez, E., Gómez, C., Rivera, G. (2014). Quality-Assessment Model for Portfolios of Projects Expressed by a Priority Ranking. 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_39

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  • DOI: https://doi.org/10.1007/978-3-319-05170-3_39

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  • Print ISBN: 978-3-319-05169-7

  • Online ISBN: 978-3-319-05170-3

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