An Optimal Portfolio Selection based on a Hybrid Approach to improve Projects Oriented Organizations
- 1 National Institute of Posts and Telecommunications, Morocco
Abstract
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.
DOI: https://doi.org/10.3844/jcssp.2018.1454.1464
Copyright: © 2018 Driss El Hannach, Rabia Marghoubi and Mohamed Dahchour. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
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Keywords
- Projects Prioritization
- Project Portfolio Selection
- Information Entropy
- Branch and Bound
- Integer Linear Programming