A New Multi-Objective Model for R&D Project Portfolio Selection Considering Potential Repetitive Projects and Sanction Impacts

نویسندگان

  • Masoud Rabbani
  • Amirhossein Najjarbashi
  • Mohammad Joudi
چکیده

In today’s highly competitive marketplace, selecting an appropriate set of projects from a portfolio of candidate projects is vital for enterprises. An accurate selection of projects can steer a company to great success, while a careless selection may lead it to bankruptcy. Variability of project parameters such as benefit, cost, risk (failure probability), etc. during planning horizon makes this selection more complicated and increases the importance of an elaborate analysis. In this article, we studied a multi-objective R&D project portfolio selection problem. There is a conflicting desire to maximize expected net benefit and minimize risk in companies. From a novel perspective, the authors considered repetitive projects and variable amounts for aforementioned project parameters during planning horizon that could be an effect of sanctions, in our model that are features of real world problems. Due to NP-hardness of the problem and its high computational effort especially when the number of projects grows, we solved test problems of different sizes using a Multi-Objective Differential Evolution (MODE) algorithm to find pareto optimal solutions. A New Multi-Objective Model for R&D Project Portfolio Selection Considering Potential Repetitive Projects and Sanction Impacts

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عنوان ژورنال:
  • IJSDS

دوره 4  شماره 

صفحات  -

تاریخ انتشار 2013