Research and development project portfolio selection under uncertainty

2017 ◽  
Vol 9 (3) ◽  
pp. 857-866 ◽  
Author(s):  
Nancy M. Arratia-Martinez ◽  
Rafael Caballero-Fernandez ◽  
Igor Litvinchev ◽  
Fernando Lopez-Irarragorri
IEEE Access ◽  
2021 ◽  
pp. 1-1
Author(s):  
Kyle Robert Harrison ◽  
Saber Elsayed ◽  
Ivan L. Garanovich ◽  
Terence Weir ◽  
Michael Galister ◽  
...  

Author(s):  
Walter J. Gutjahr ◽  
Stefan Katzensteiner ◽  
Peter Reiter ◽  
Christian Stummer ◽  
Michaela Denk

2021 ◽  
Vol 27 (2) ◽  
pp. 493-510
Author(s):  
Samaneh Zolfaghari ◽  
Seyed Meysam Mousavi ◽  
Jurgita Antuchevičienė

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.


2020 ◽  
Vol 11 (2) ◽  
pp. 41-70
Author(s):  
Nantasak Tansakul ◽  
Pisal Yenradee

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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