A comprehensive mathematical model for resource-constrained multi-objective project portfolio selection and scheduling considering sustainability and projects splitting

2020 ◽  
Vol 269 ◽  
pp. 122073
Author(s):  
Ali RezaHoseini ◽  
Seyed Farid Ghannadpour ◽  
Maryam Hemmati
Keyword(s):  
Mathematical Model ◽  
Portfolio Selection ◽  
Project Portfolio ◽  
Resource Constrained ◽  
Multi Objective ◽  
Project Portfolio Selection

scholarly journals Multi objective project portfolio selection

2019 ◽  
pp. 249-256 ◽  
Author(s):  
Kamal Baqeri ◽  
Emran Mohammadi ◽  
Mahsa Mofrad Gilani
Keyword(s):  
Portfolio Selection ◽  
Project Portfolio ◽  
Multi Objective ◽  
Project Portfolio Selection

Optimal project portfolio selection with reinvestment strategy considering sustainability in an uncertain environment: a multi-objective optimization approach

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Mohammadali Zarjou ◽  
Mohammad Khalilzadeh
Keyword(s):  
Mathematical Programming ◽  
Portfolio Selection ◽  
Programming Model ◽  
Sustainability Indicators ◽  
Selection Problem ◽  
Project Portfolio ◽  
Mathematical Programming Model ◽  
Content Type ◽  
Multi Objective ◽  
Project Portfolio Selection

PurposeThis study aims to develop a model for project portfolio selection considering organizational goals such as budgets, sustainability cash flow and reinvestment strategy under an uncertain environment.Design/methodology/approachA multi-objective mathematical programming model is proposed for project selection, which takes the social, environmental and financial aspects into account as the objectives of the project portfolio selection problem. The project evaluation and selection process in one of the large capitals in the Middle East with numerous urban construction projects was considered as a real case study, in which the subjects of environmental and social sustainability are of great importance. Then, the most significant criteria for project evaluation and selection based on sustainability were identified and ranked using the fuzzy best-worst method (BWM).FindingsThe criterion of “defining clear and real objectives” was ranked first, “project investment return period” was ranked second, “minimum changes in the predicted range” was ranked third, and the other ten sustainability indicators were ranked as well. Next, the presented mathematical programming model was solved using the augmented e-constraint method. The sensitivity analysis indicated that increasing the amount of investments in projects would increase their net present value. Also, increased investment had no effect on sustainability, while decreased investment caused sustainability to not being optimal.Originality/valueThis study focuses on the impact of the amount of investments on projects, and the associated costs of sustainable projects. Further to the authors' knowledge, there has been no relevant study taking uncertainty into account. Also, very few studies proposed a mathematical programming model for the project portfolio selection problem. Moreover, this research uses the brainstorming and Delphi method to identify the sustainability indicators influencing the organization and screens the evaluation indicators. Furthermore, the weights of the evaluation indicators are determined using the fuzzy BWM based on the consistency of opinions.

A New Multi-Objective Model for R&D Project Portfolio Selection Considering Potential Repetitive Projects and Sanction Impacts

2013 ◽  
Vol 4 (4) ◽  
pp. 41-54 ◽  
Author(s):  
Masoud Rabbani ◽  
Amirhossein Najjarbashi ◽  
Mohammad Joudi
Keyword(s):  
Portfolio Selection ◽  
Planning Horizon ◽  
Computational Effort ◽  
Test Problems ◽  
Great Success ◽  
Project Portfolio ◽  
Net Benefit ◽  
Multi Objective ◽  
Project Portfolio Selection ◽  
Benefit Cost

In today’s highly competitive marketplace, selecting an appropriate set of projects from a portfolio of candidate projects is vital for enterprises. An accurate selection of projects can steer a company to great success, while a careless selection may lead it to bankruptcy. Variability of project parameters such as benefit, cost, risk (failure probability), etc. during planning horizon makes this selection more complicated and increases the importance of an elaborate analysis. In this article, we studied a multi-objective R&D project portfolio selection problem. There is a conflicting desire to maximize expected net benefit and minimize risk in companies. From a novel perspective, the authors considered repetitive projects and variable amounts for aforementioned project parameters during planning horizon that could be an effect of sanctions, in our model that are features of real world problems. Due to NP-hardness of the problem and its high computational effort especially when the number of projects grows, we solved test problems of different sizes using a Multi-Objective Differential Evolution (MODE) algorithm to find pareto optimal solutions.

scholarly journals A Multiagent Evolutionary Algorithm for the Resource-Constrained Project Portfolio Selection and Scheduling Problem

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
Yongyi Shou ◽  
Wenwen Xiang ◽  
Ying Li ◽  
Weijian Yao
Keyword(s):  
Evolutionary Algorithm ◽  
Portfolio Selection ◽  
Level Structure ◽  
Project Portfolio ◽  
Scheduling Problem ◽  
Resource Constrained ◽  
Project Portfolio Selection ◽  
Multiproject Scheduling ◽  
Upper Level ◽  
Self Learning

A multiagent evolutionary algorithm is proposed to solve the resource-constrained project portfolio selection and scheduling problem. The proposed algorithm has a dual level structure. In the upper level a set of agents make decisions to select appropriate project portfolios. Each agent selects its project portfolio independently. The neighborhood competition operator and self-learning operator are designed to improve the agent’s energy, that is, the portfolio profit. In the lower level the selected projects are scheduled simultaneously and completion times are computed to estimate the expected portfolio profit. A priority rule-based heuristic is used by each agent to solve the multiproject scheduling problem. A set of instances were generated systematically from the widely used Patterson set. Computational experiments confirmed that the proposed evolutionary algorithm is effective for the resource-constrained project portfolio selection and scheduling problem.

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