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 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.

A scenario-based mathematical approach to a robust project portfolio selection problem under fuzzy uncertainty

2021 ◽  
pp. 1-14
Author(s):  
Saeed Karimi ◽  
Saeed Mirzamohammadi ◽  
MirSaman Pishvaee
Keyword(s):  
Portfolio Selection ◽  
Confidence Level ◽  
Optimization Model ◽  
Selection Problem ◽  
Programming Approach ◽  
Project Portfolio ◽  
Portfolio Selection Problem ◽  
Project Portfolio Selection ◽  
Proposed Model ◽  
Uncertainty Of Parameters

As a major concern of chief managers in each organization, project portfolio selection has a special place in their responsibilities. To assist managers in making decisions, applicable optimization models play an essential role in such processes. In this regard, this paper provides a stochastic optimization model for a project portfolio selection problem under different scenarios. Providing the novelty in the model along with making it closer to reality, the interdependency between revenue and cost of projects is considered. Due to the inherent uncertainty of parameters, the revenue and cost of each project, as well as contributed capital, follow triangular fuzzy parameters. Contrary to the previous model, the appreciation of assets is considered in the proposed model as the other novelty of the proposed model. To tackle the uncertainty of parameters, a robust possibilistic approach is used, which has been first-ever devised in such problems. Being both optimistic and pessimistic approaches available for decision-makers, a new measure is introduced to make the model inclusive. Moreover, by considering the confidence level as both parameter and decision variables, the robust possibilistic programming approach is adopted to solve the proposed model. Using the new proposed measure, the optimal average value of robust model are obtained under different confidence level. Finally, solving the optimization model, the results are provided by implementing the realization for uncertain parameters, and regarding the obtained results, discussions are made to provide some insights to the managers.

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

CREDIBILITY-BASED FUZZY MATHEMATICAL PROGRAMMING MODEL FOR PORTFOLIO SELECTION UNDER UNCERTAINTY

2014 ◽  
Vol 13 (01) ◽  
pp. 101-135 ◽  
Author(s):  
MUKESH KUMAR MEHLAWAT ◽  
PANKAJ GUPTA
Keyword(s):  
Mathematical Programming ◽  
Portfolio Selection ◽  
Programming Model ◽  
Fuzzy Optimization ◽  
Chance Constrained Programming ◽  
Fuzzy Mathematical Programming ◽  
Mathematical Programming Model ◽  
Two Phase ◽  
Solution Approach ◽  
Practical Applications

In this paper, we develop a hybrid bi-objective credibility-based fuzzy mathematical programming model for portfolio selection under fuzzy environment. To deal with imprecise parameters, we use a hybrid credibility-based approach that combines the expected value and chance constrained programming techniques. The model simultaneously maximizes the portfolio return and minimizes the portfolio risk. We also consider an additional important criterion, namely, portfolio liquidity as a constraint in the model to make it better suited for practical applications. The proposed fuzzy optimization model is solved using a two-phase approach. An empirical study is included to demonstrate applicability of the proposed model and the solution approach in real-world applications of portfolio selection.

Sign in / Sign up

Export Citation Format

Share Document