A Grey Theory Based Multiple Attribute Approach for R&D Project Portfolio Selection

Abstract

In this paper, the research and development (R&D) project portfolio selection problem is introduced as a multiple attribute decision making problem. Recognizing and modeling the project interdependencies provide valuable cost savings and other greater benefits to organizations. Therefore, besides conventional attributes like cost and outcome, different type of interdependencies are also considered as attributes. Since the decision makers’ preferences on the project alternatives or attributes are uncertain, a grey theory based method is proposed to cope with the uncertainty. correspondingly, the preferences and ratings of the attributes are described by linguistic variables, which are further expressed as grey numbers. Consequently, a ranking order of the projects is done using grey possibility degree and is used to determine the portfolio. To explore, an illustration is done by a case study. The methodology proposed here is shown to be an efficient approach to solve the R&D project portfolio selection problem.