Project Portfolio Management (PPM) is an essential component of an organisation’s strategic procedures, which requires attention of several factors to envisage a range of long-term outcomes to support strategic project portfolio decisions. To evaluate overall efficiency at the portfolio level, it is essential to identify the functionality of specific projects as well as to aggregate those findi...

This paper considers a portfolio selection problem with type-2 fuzzy future returns involving ambiguous and subjectivity. Since this proposed problem is not well-defined due to fuzziness, introducing the fuzzy goal for the total future return and the degree of possibility, the main problem is transformed into the standard fuzzy programming problem including the secondary fuzzy numbers. Furtherm...

We present a fuzzy version of the efficient portfolio selection problem which adds to the Markowitz’s classical model the vagueness of the investor’s preferences about the assumed risk. This is done by adapting some techniques previously applied by the authors in other logistic problems. We provide several procedures to solve it: an exact one and a hybrid meta-heuristic procedure more adequate ...

In this paper we combine Real Options (ROs), Analytic Hierarchy Process (AHP) and zero-one Goal Programming (ZOGP) in an integrated decision analysis framework for valuing and prioritizing a portfolio of ICT infrastructure investments. It is the first time that ROs are integrated with AHP and ZOGP providing a single multi-objective multi-criteria model, called GROAHP. Finally, a case illustrati...

Dealing with ill-defined problems, where the actual values of input parameters are unknown or not directly measurable, is generally not an easy task. In this paper, we propose a hybrid metaheuristic approach, incorporating a sampling-based simulation module, in order to enhance the robustness of the final solutions. Empirical application to the classical mean-variance portfolio optimization pro...

A hierarchical framework is proposed to address the issues of modeling different type of words in keyword spotting (KWS). Keyword models are built at various levels according to the availability of training set resources for each individual word. The proposed approach improves the performance of KWS even when no training speech is available for the keywords. It also suggests an easier way to co...