Research Article Open Access

An Optimal Portfolio Selection based on a Hybrid Approach to improve Projects Oriented Organizations

Driss El Hannach1, Rabia Marghoubi1 and Mohamed Dahchour1
  • 1 National Institute of Posts and Telecommunications, Morocco


Nowadays, managing and allocating resources to the project portfolio is one of the most critical decision-making processes in project-oriented organizations. To achieve the most value in terms of profitability, these companies should consider taking advantage of ongoing projects and optimal management of their resources allocated to the most optimal project portfolio. Project Portfolio Selection (PPS) and resource allocation are critical problems in project portfolio based companies. These organizations are required to evaluate, prioritize and select their projects in accordance with the strategic and operational mission and objectives. In this study, we propose a three-stage hybrid approach for prioritizing and selecting an optimal project portfolio. We obtain the maximum economic contribution (maximum fitness) between the final PPS and the projects initial prioritizing while considering various organizational criteria and objectives. The proposed approach is composed of three stages with several steps. We use information entropy for the initial prioritizing, the branch and bound algorithm for generating combination of project portfolios and Integer Linear Programming (ILP) for selecting the most suitable project portfolio according to strategic and operational objectives. At the end, a case study is used to demonstrate the applicability and the merits of the proposed approach.

Journal of Computer Science
Volume 14 No. 11, 2018, 1454-1464


Submitted On: 1 July 2018 Published On: 7 November 2018

How to Cite: El Hannach, D., Marghoubi, R. & Dahchour, M. (2018). An Optimal Portfolio Selection based on a Hybrid Approach to improve Projects Oriented Organizations. Journal of Computer Science, 14(11), 1454-1464.

  • 2 Citations



  • Projects Prioritization
  • Project Portfolio Selection
  • Information Entropy
  • Branch and Bound
  • Integer Linear Programming