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.
Highlights
Employees are confronted with decisions in their professional life
They can use conventional approaches such as the weighted sum. This approach is not refined because it assumes a linearity of preferences that does not reflect the preferences of decision makers
We propose hybrid approach to first prioritize projects using information entropy and second generating feasible portfolios and build the optimal portfolio using mathematical programming while respecting the constraints of the resources put at our disposal
Summary
Employees are confronted with decisions in their professional life. A manager in an organization needs to evaluate suppliers to develop partnerships with the best. Liu and Wang (2011) developed an optimization model for the project selection and scheduling problem based on the Constraint Programming (CP) method using time-dependent resource constraints. Tavana et al (2015) proposed a method for selecting an optimal combination of projects They use respectively in a fuzzy environment the Data Envelopment Analysis (DEA), the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and ILP. Our approach will use information entropy, branch and bound algorithm and mathematical programming which will prevent scalability, time consumption and the difficulty of implementation From this comparative study, we can deduce that our approach has a positive impact on time, ease of implementation and reducing the complexity of the PPS problem.
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
