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Article history: Received: August 2 2019 Received in revised format: August 2 2019 Accepted: August 26 2019 Available online: August 27 2019 Over the past four decades, portfolio selection has been one of the most important concerns of researchers, project managers, project-oriented companies, and public agencies around the world. Although numerous studies have been done in this field, still there is a room for more improvement in both theory and practice. One of the yet unspoiled topics in this field is improving and balancing the efficiency of sub-portfolios while paying attention to portfolio optimization. This study employs data-mining tools to categorize projects into sub-portfolios and rank them. Multiple Criteria Decision Making (MCDM) methods are also used to weigh the criteria on which the ranking process is based. Finally, a novel multi-objective model is designed to optimize the efficiency of sub-portfolios and the gain of the main portfolio. The model is solved by NSGA II algorithm. This study introduces a hybrid framework by which project portfolio selection process can be carried out regarding strategic alignment, cost, and risk. © 2020 by the authors; licensee Growing Science, Canada.

Selecting a portfolio of projects considering both optimization and balance of sub-portfolios