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PROJECT PORTFOLIO SELECTION PROBLEMS: A REVIEW OF MODELS, UNCERTAINTY APPROACHES, SOLUTION TECHNIQUES, AND CASE STUDIES
Author(s) -
Vahid Mohagheghi,
Seyed Meysam Mousavi,
Jurgita Antuchevičienė,
Mohammad Mojtahedi
Publication year - 2019
Publication title -
technological and economic development of economy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.634
H-Index - 47
eISSN - 2029-4921
pISSN - 2029-4913
DOI - 10.3846/tede.2019.11410
Subject(s) - portfolio , selection (genetic algorithm) , project portfolio management , management science , computer science , heuristics , application portfolio management , portfolio optimization , modern portfolio theory , operations research , process (computing) , risk analysis (engineering) , data science , project management , economics , artificial intelligence , business , engineering , finance , management , operating system
Project portfolio selection has been the focus of many scholars in the last two decades. The number of studies on the strategic process has significantly increased over the past decade. Despite this increasing trend, previous studies have not been yet critically evaluated. This paper, therefore, aims to presents a comprehensive review of project portfolio selection and optimization studies focusing on the evaluation criteria, selection approach, solution approach, uncertainty modeling, and applications. This study reviews more than 140 papers on project portfolio selection research topic to identify the gaps and to present future trends. The findings show that not only the financial criteria but also social and environmental aspects of project portfolios have been focused by researchers in project portfolio selection in recent years. In addition, meta-heuristics and heuristics approach to finding the solution of mathematical models have been the critical research by scholars. Expert systems, artificial intelligence, and big data science have not been considered in project portfolio selection in the previous studies. In future, researchers can investigate the role of sustainability, resiliency, foreign investment, and exchange rates in project portfolio selection studies, and they can focus on artificial intelligence environments using big data and fuzzy stochastic optimization techniques.

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