Project portfolio selection and planning with fuzzy constraints

Franco, Pérez; Gómez, Trinidad; Caballero, Rafael; Liern, Vicente

doi:10.1016/j.techfore.2017.07.012

Cited by 70 publications

(25 citation statements)

References 45 publications

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“…Fuzzy Programming: selecting projects based on fuzzy expressions. (Ghapanchi, et al, 2012) (Pérez, et al, 2018) DEA + QFD QFD Method: all customer requirements and needs are identified and effectively transmitted to different parts of the organization. DEA: determines the efficient frontier (Jafarzadeh, et al, 2018) MCDM+ IP + DEA MCDM: Ranking the strategies IP: selecting projects based on the strategy weights and alignments.…”

Section: Decision Treementioning

confidence: 99%

Selecting a portfolio of projects considering both optimization and balance of sub-portfolios

Raad¹,

Shirazi²,

Ghodsypour³

2020

10.5267/j.jpm

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Over the past four decades, portfolio selection has been one of the most important concerns of researchers, project managers, project-oriented companies, and public agencies around the world. Although numerous studies have been done in this field, still there is a room for more improvement in both theory and practice. One of the yet unspoiled topics in this field is improving and balancing the efficiency of sub-portfolios while paying attention to portfolio optimization. This study employs data-mining tools to categorize projects into sub-portfolios and rank them. Multiple Criteria Decision Making (MCDM) methods are also used to weigh the criteria on which the ranking process is based. Finally, a novel multi-objective model is designed to optimize the efficiency of sub-portfolios and the gain of the main portfolio. The model is solved by NSGA II algorithm. This study introduces a hybrid framework by which project portfolio selection process can be carried out regarding strategic alignment, cost, and risk.

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Section: Decision Treementioning

confidence: 99%

Selecting a portfolio of projects considering both optimization and balance of sub-portfolios

Raad¹,

Shirazi²,

Ghodsypour³

2020

10.5267/j.jpm

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“…Furthermore, [25] supposed that the projects can start in some periods and continuing or not over following periods in order to maximise the benefits derived from the portfolio and the balance of the resources allocated in the different periods. Recently, [50] modeled synergies and incompatibilities among projects and uncertainty in the parameters of the problem.…”

Section: Introductionmentioning

confidence: 99%

A general space-time model for combinatorial optimization problems (and not only)

Barbati

Corrente

Greco

2020

Omega

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We consider the problem of defining a strategy consisting of a set of facilities taking into account also the location where they have to be assigned and the time in which they have to be activated. The facilities are evaluated with respect to a set of criteria. The plan has to be devised respecting some constraints related to different aspects of the problem such as precedence restrictions due to the nature of the facilities. Among the constraints, there are some related to the available budget. We consider also the uncertainty related to the performances of the facilities with respect to considered criteria, and plurality of stakeholders participating to the decision. The considered problem can be seen as the combination of some prototypical operations research problems: knapsack problem, location problem and project scheduling. Indeed, the basic brick of our model is a variable x ilt which takes value 1 if facility i is activated in location l at time t, and 0 otherwise. Due to the conjoint consideration of a location and a time in the decision variables, what we propose can be seen as a general space-time model for operations research problems. We discuss how such a model permits to handle complex problems using several methodologies including multiple attribute value theory and multiobjective optimization. With respect to the latter point, without any loss of the generality, we consider the compromise programming and an interactive methodology based on the Dominance-based Rough Set Approach. We illustrate the application of our model with a simple didactic example.

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“…Mohanty et al [6] employed fuzzy methods using the ANP to deal with a fuzzy cost analysis and Carlsson et al [7] proposed a fuzzy mixed-integer programming model for an R&D project selection problem. Pérez et al [8] considered the uncertainty designed by fuzzy techniques to assist decision-makers with selection project portfolio selection and scheduling. Mohagheghi et al [9] applied interval type-2 fuzzy sets to deal with uncertainty.…”

Section: Introductionmentioning

confidence: 99%

Project Portfolio Selection Considering Total Cost of Ownership in the Automobile Industry

Lee

Choi

2019

Sustainability

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Project portfolio selection for developing a new product is critical to a company because the attributes of the project reflect on the price, quality, and functionality of the developed product. The market evaluates the developed product and the assessment of the product value determines its sale on the market. The project portfolio selection and sales are interconnected from a corporate perspective. The automobile industry is an industry which responds to the issue of business sustainability sensitively because their business directly relates to the environment. In this study, business sustainability was approached through the perspective of total cost of ownership (TCO) embedded into the project selection model after the attributes of the project, investment and efficiency, and the TCO of the product were combined to generate a sales function. The sales and revenue models were proposed, and the validity of the models was confirmed using a case from the automobile industry. As a result of the experiments, the sales model tended to show that the market share increased by selecting the proper number of projects to maximize sales. In contrast, the revenue model showed a tendency to select projects more than the sales model in order to maximize the profits of the company. By suggesting project selection models in a new perspective different from the ones in existing studies, this study is valuable with regard to the fact that the suggested models preserve project interrelationships, TCO, and product sales in a practical manner to enhance business sustainability.

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Project portfolio selection and planning with fuzzy constraints

Cited by 70 publications

References 45 publications

Selecting a portfolio of projects considering both optimization and balance of sub-portfolios

Selecting a portfolio of projects considering both optimization and balance of sub-portfolios

A general space-time model for combinatorial optimization problems (and not only)

Project Portfolio Selection Considering Total Cost of Ownership in the Automobile Industry

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