A robust algorithm for project portfolio selection problem using real options valuation

Purpose The principal concern of organization managers in the global rivalry of commerce environment is how to select the project portfolio among available projects. In this matter, organizations should consider the uncertainty intrinsic in the projects regarding an appropriate valuation technique within an optimization framework. In this research, the purpose of this paper is to formulate using a robust optimization algorithm to deal with the complexities and uncertainty inherent in the construction of the project portfolio. Design/methodology/approach First, a general mathematical formulation is presented, which in compound real options valuation is highlighted. This formulation gives managerial flexibility by correcting the deficiency of traditional discounted cash flow technique that excludes any form of flexibility. Then, considering a limitation on budget of the organization, an integer programming formulation to maximize the n-fold compound options for project portfolio selection is proposed. Finally, a robust optimization model is developed along with the robust combinatorial optimization algorithm, which is effective for solving problems under uncertainty. Findings Sensitivity analysis showed that projects in later phases of development, having survived several phases of pre-clinical and clinical tests, are worth more because they are more likely to pertain to business. However, the investment costs related to each project during development phases limit the number of projects that a company can bring to their final portfolio. Additionally, the analysis of conservatism level represented how project managers can quite easily determine their risk attitude and the corresponding portfolio composition. From a managerial point of view, the proposed framework is very useful because it requires only financial estimates. Hence, the proposed decision support tool can assist research and development (R&D) project managers in the pharmaceutical industry for making decisions. Originality/value The first is the application of the n-fold compound options on portfolio of R&D projects and the employment of compound options value of a project portfolio as an objective function. The second one is a mathematical formulation of these concepts and solving it by the robust combinatorial optimization algorithm. The literature is lacking in the application of the robust combinatorial optimization algorithm to R&D project portfolio selection based on the generalized n-fold compound option model of Cassimon et al. (2004). Every framework from calculation of the n-fold compound option to solving robust combinatorial algorithm is programmed in Matlab software, since it can be used as a business support tool.

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A project portfolio selection framework for transforming Iranian universities into entrepreneurial institutions

Journal of Industry-University Collaboration ◽

10.1108/jiuc-06-2019-0014 ◽

2020 ◽

Vol 2 (1) ◽

pp. 2-21

Author(s):

Nima Golghamat Raad ◽

Mohsen Akbarpour Shirazi

Keyword(s):

Portfolio Selection ◽

Project Portfolio ◽

Risk Minimization ◽

Content Type ◽

Project Portfolio Selection ◽

Performance Matrix ◽

University Of Technology ◽

Objective Model ◽

Selection Framework ◽

Almost All

PurposeThis research proposes a framework by which universities can define and implement projects that transform them into entrepreneurial universities. The framework helps decision-makers identify suitable goals and strategies, gather a list of projects to fulfill the goals and strategies and prioritize the projects and form a portfolio.Design/methodology/approachIn the proposed framework, importance–performance matrix, hierarchical strategic planning, Delphi technique, DEMATEL-based ANP and a multi-objective model are used. The mathematical model consists of four objective functions including efficiency, quality and balance maximization and also cost and risk minimization. The proposed framework is applied to Amirkabir University of Technology, Tehran, Iran, and the results are brought in this paper.FindingsThe output of the proposed framework is a portfolio of projects that aims to transform a traditional university into a third-generation one. Although the final portfolio must be customized for different universities, the proposed steps of the framework can be helpful for almost all cases.Originality/valueThe suggested framework is unique and uses both qualitative and quantitative techniques for project portfolio selection.

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A hybrid grey based artificial neural network and C&R tree for project portfolio selection

Benchmarking An International Journal ◽

10.1108/bij-06-2016-0087 ◽

2017 ◽

Vol 24 (3) ◽

pp. 651-665 ◽

Cited By ~ 5

Author(s):

Farshad Faezy Razi ◽

Seyed Hooman Shariat

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Decision Tree ◽

Portfolio Selection ◽

Grey Relational Analysis ◽

Project Portfolio ◽

Content Type ◽

Relational Analysis ◽

Project Portfolio Selection ◽

Grey Relational

Purpose The purpose of this paper is twofold: the selection of project portfolios through hybrid artificial neural network algorithms, feature selection based on grey relational analysis, decision tree and regression; and the identification of the features affecting project portfolio selection using the artificial neural network algorithm, decision tree and regression. The authors also aim to classify the available options using the decision tree algorithm. Design/methodology/approach In order to achieve the research goals, a project-oriented organization was selected and studied. In all, 49 project management indicators were chosen from A Guide to the Project Management Body of Knowledge (PMBOK Guide), and the most important indicators were identified using a feature selection algorithm and decision tree. After the extraction of rules, decision rule-based multi-criteria decision making matrices were produced. Each matrix was ranked through grey relational analysis, similarity to ideal solution method and multi-criteria optimization. Finally, a model for choosing the best ranking method was designed and implemented using the genetic algorithm. To analyze the responses, stability of the classes was investigated. Findings The results showed that projects ranked based on neural network weights by the grey relational analysis method prove to be better options for the selection of a project portfolio. The process of identification of the features affecting project portfolio selection resulted in the following factors: scope management, project charter, project management plan, stakeholders and risk. Originality/value This study presents the most effective features affecting project portfolio selection which is highly impressive in organizational decision making and must be considered seriously. Deploying sensitivity analysis, which is an innovation in such studies, played a constructive role in examining the accuracy and reliability of the proposed models, and it can be firmly argued that the results have had an important role in validating the findings of this study.

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The evolution of project portfolio selection methods: from incremental to radical innovation

Revista de Gestão ◽

10.1108/rege-10-2018-0096 ◽

2019 ◽

Vol 26 (3) ◽

pp. 212-236 ◽

Cited By ~ 2

Author(s):

Ximena Alejandra Flechas Chaparro ◽

Leonardo Augusto de Vasconcelos Gomes ◽

Paulo Tromboni de Souza Nascimento

Keyword(s):

Portfolio Selection ◽

Research Question ◽

Radical Innovation ◽

Project Portfolio ◽

Content Type ◽

Project Portfolio Selection ◽

Information Gap ◽

Innovation Projects ◽

Selection Framework ◽

Comprehensive Framework

Purpose The purpose of this paper is to identify how project portfolio selection (PPS) methods have evolved and which approaches are more suitable for radical innovation projects. This paper addressed the following research question: how have the selection approaches evolved to better fit within radical innovation conditions? The current literature offers a number of selection approaches with different and, in some cases, conflicting nature. Therefore, there is a lack of understanding regarding when and how to use these approaches in order to select a specific type of innovation projects (from incremental to more radical ones). Design/methodology/approach Given the nature of the research question, the authors perform a systematic literature review method and analyze 48 portfolio selection approaches. The authors then classified and characterized these articles in order to identify techniques, tools, required data and types of examined projects, among other aspects. Findings The authors identify four key features related to the selection of radical innovation projects: dynamism, interdependency management, uncertainty treatment and required input data. Based on the content analysis, the authors identified that approaches based on different sources and nature of data are more appropriated for uncertain conditions, such as behavioral methods, information gap theory, real options and integrated approaches. Originality/value The research provides a comprehensive framework about PPS methods and how they have been evolving over time. This portfolio selection framework considers the particular aspects of incremental and radical innovation projects. The authors hope that the framework contributes to reinvigorating the literature on selection approaches for innovation projects.

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

Kybernetes ◽

10.1108/k-11-2020-0737 ◽

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.

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

IEEE Access ◽

10.1109/access.2021.3086070 ◽

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

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Competence-driven project portfolio selection, scheduling and staff assignment

Central European Journal of Operations Research ◽

10.1007/s10100-008-0081-z ◽

2009 ◽

Cited By ~ 1

Author(s):

Walter J. Gutjahr ◽

Stefan Katzensteiner ◽

Peter Reiter ◽

Christian Stummer ◽

Michaela Denk

Keyword(s):

Portfolio Selection ◽

Project Portfolio ◽

Project Portfolio Selection ◽

Staff Assignment

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

Technological and Economic Development of Economy ◽

10.3846/tede.2021.14652 ◽

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.

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