scholarly journals PROJECT PORTFOLIO SELECTION PROBLEMS: A REVIEW OF MODELS, UNCERTAINTY APPROACHES, SOLUTION TECHNIQUES, AND CASE STUDIES

2019 ◽  
Vol 25 (6) ◽  
pp. 1380-1412 ◽  
Author(s):  
Vahid Mohagheghi ◽  
Seyed Meysam Mousavi ◽  
Jurgita Antuchevičienė ◽  
Mohammad Mojtahedi
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Portfolio Selection ◽  
Data Science ◽  
Evaluation Criteria ◽  
Uncertainty Modeling ◽  
Optimization Techniques ◽  
Project Portfolio ◽  
Solution Approach ◽  
Project Portfolio Selection

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.

scholarly journals A TYPE-2 FUZZY OPTIMIZATION MODEL FOR PROJECT PORTFOLIO SELECTION AND SCHEDULING INCORPORATING PROJECT INTERDEPENDENCY AND SPLITTING

2021 ◽  
Vol 27 (2) ◽  
pp. 493-510
Author(s):  
Samaneh Zolfaghari ◽  
Seyed Meysam Mousavi ◽  
Jurgita Antuchevičienė
Keyword(s):  
Portfolio Selection ◽  
Optimization Model ◽  
Fuzzy Optimization ◽  
Project Portfolio ◽  
Time Value Of Money ◽  
Solution Approach ◽  
Project Portfolio Selection ◽  
The Interest Rate ◽  
Interval Type

This paper presents a new optimization model and a new interval type-2 fuzzy solution approach for project portfolio selection and scheduling (PPSS) problem, in which split of projects and re-execution are allowable. Afterward, the approach is realized as a multi-objective optimization that maximizes total benefits of projects concerning economic concepts by considering the interest rate and time value of money and minimizes the tardiness value and total number of interruptions of chosen projects. Besides, budget and resources limitation, newfound relations are proposed to consider dependency relationships via a synergy among projects to solve PPSS problem hiring interval type-2 fuzzy sets. For validation of the model, numerical instances are provided and solved by a new extended procedure based on fuzzy optimistic and pessimistic viewpoints regarding several situations. In the end, their results are studied. The results show that it is more beneficial when projects are allowed to be split.

scholarly journals A Hybrid Multi-Population Approach to the Project Portfolio Selection and Scheduling Problem for Future Force Design

IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Kyle Robert Harrison ◽  
Saber Elsayed ◽  
Ivan L. Garanovich ◽  
Terence Weir ◽  
Michael Galister ◽  
...  
Keyword(s):  
Portfolio Selection ◽  
Project Portfolio ◽  
Scheduling Problem ◽  
Population Approach ◽  
Project Portfolio Selection

scholarly journals Competence-driven project portfolio selection, scheduling and staff assignment

2009 ◽  
Author(s):  
Walter J. Gutjahr ◽  
Stefan Katzensteiner ◽  
Peter Reiter ◽  
Christian Stummer ◽  
Michaela Denk
Keyword(s):  
Portfolio Selection ◽  
Project Portfolio ◽  
Project Portfolio Selection ◽  
Staff Assignment

Data Science: Big Data, Machine Learning, and Artificial Intelligence

2018 ◽  
Vol 15 (3) ◽  
pp. 497-498 ◽  
Author(s):  
Ruth C. Carlos ◽  
Charles E. Kahn ◽  
Safwan Halabi
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Big Data ◽  
Data Science

The Nature of Intelligent Analytics

2021 ◽  
pp. 1-21
Author(s):  
Zhaohao Sun ◽  
Andrew Stranieri
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Research And Development ◽  
Business Intelligence ◽  
Data Analytics ◽  
Data Science ◽  
Big Data Analytics ◽  
Business Analytics ◽  
Novel Approach ◽  
Advanced Analytics

Intelligent analytics is an emerging paradigm in the age of big data, analytics, and artificial intelligence (AI). This chapter explores the nature of intelligent analytics. More specifically, this chapter identifies the foundations, cores, and applications of intelligent big data analytics based on the investigation into the state-of-the-art scholars' publications and market analysis of advanced analytics. Then it presents a workflow-based approach to big data analytics and technological foundations for intelligent big data analytics through examining intelligent big data analytics as an integration of AI and big data analytics. The chapter also presents a novel approach to extend intelligent big data analytics to intelligent analytics. The proposed approach in this chapter might facilitate research and development of intelligent analytics, big data analytics, business analytics, business intelligence, AI, and data science.

Fuzzy Improvement-Project Portfolio Selection Considering Financial Performance and Customer Satisfaction

2020 ◽  
Vol 11 (2) ◽  
pp. 41-70
Author(s):  
Nantasak Tansakul ◽  
Pisal Yenradee
Keyword(s):  
Portfolio Selection ◽  
Employee Satisfaction ◽  
Significant Contribution ◽  
Fuzzy Numbers ◽  
Practical Method ◽  
Project Portfolio ◽  
Favorable Result ◽  
Triangular Fuzzy Numbers ◽  
Improvement Project ◽  
Project Portfolio Selection

This article develops a suitable and practical method for improvement-project portfolio selection under uncertainty, based on the requirements of a bank in Thailand. A significant contribution of this article is that the proposed method can determine an optimal project portfolio, to satisfy the customer/employee satisfaction targets and an investment budget constraint. This allows users to estimate parameters as triangular fuzzy numbers under pessimistic, most likely, and optimistic situations. Four mathematical models are proposed to maximize the defuzzified values of fuzzy NPV and fuzzy BCR, and to maximize the possibility that the project portfolio is economically justified under fuzzy situations of NPV and BCR. Results reveal that maximizing the defuzzified value of fuzzy NPV offers the most favorable result since it maximizes the current wealth of the bank. Additionally, the possibility that the entire project portfolio is economically justified under all fuzzy situations is relatively high for all numerical cases.

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