Using multicriteria analysis and fuzzy logic for project portfolio management (original) (raw)
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Evaluation and Program Planning, 2019
The primary goal in project portfolio management is to select and manage the optimal set of projects that contribute the maximum in business value. However, selecting Information Technology (IT) projects is a difficult task due to the complexities and uncertainties inherent in the strategic-operational nature of the process, and the existence of both quantitative and qualitative criteria. We propose a two-stage process to select an optimal project portfolio with the aim of maximizing project benefits and minimizing project risks. We construct a twostage hybrid mathematical programming model by integrating Fuzzy Analytic Hierarchy Process (FAHP) with Fuzzy Inference System (FIS). This hybrid framework provides the ability to consider both the quantitative and qualitative criteria while considering budget constraints and project risks. We also present a real-world case study in the cybersecurity industry to exhibit the applicability and demonstrate the efficacy of our proposed method. Ghorbaniane (2015) show that often multi-criteria decision making (MDCM) models, mathematical models, or a combination of both are used to solve project portfolio selection problems. In the following, the project portfolio selection literature is explored with reference to MCDM methods, mathematical models, and combination of the two. MCDM methods are commonly used to rank multiple alternatives according to multiple and often conflicting criteria (Mina, Mirabedini, Kian, & Ghaderi, 2014), thus making them suitable for solving project portfolio selection problems with complex and conflicting criteria. According to Wu, Zhang, Xu, and Li (2018), MCDM models are widely used for project evaluation and ranking. Han, Kim, Choi, and Kim
Best selection of project portfolio using Fuzzy AHP and Fuzzy TOPSIS
Journal of Engineering Management and Competitiveness
Choosing the optimal portfolio for the project is one of the most important and strategic decisions in most organizations, especially project-based organizations. The issue of the project selection is a periodic activity in order to choose the appropriate and optimal portfolio from the proposed projects and ongoing projects within the organization which can meet organizational goals without waste of the resources and taking into account certain constraints. Consequently, the aim of this paper is to select the best project portfolio by using fuzzy AHP and fuzzy TOPSIS methods. The forgoing methods have been used in a case study, and the result and data have been evaluated from different points of view.
2014 9th Iberian Conference on Information Systems and Technologies (CISTI), 2014
This paper presents an approach to solve project portfolio selection problem (PPSP) in the presence of limited resources, multiples criteria, software projects, constraints, functions to be optimized, interdependent projects, and scenarios with a large number of projects available. For this purpose, it is divided into two phases, one for (i) optimization using the multiobjective algorithm NSGA-II and another (ii) postoptimization using the Analytic Hierarchy Process (AHP). Among their contributions, we can name (i) a solution to the combinatorial analysis 2 n and (ii) the structure of a hierarchy of criteria derived from subjective aspects.
A hybrid fuzzy rule-based multi-criteria framework for sustainable project portfolio selection
Information Sciences, 2013
Project selection is a complex decision making process that is influenced by multiple and often conflicting objectives. The complexity of the project selection problem is due to the high number of projects from which a subset (portfolio) has to be chosen. We present a hybrid fuzzy rule-based multi-objective framework for sustainable project portfolio selection. The multiple and conflicting objectives are considered as the input variables in a Fuzzy Rule-Based (FRB) system developed to estimate the overall fitness (suitability) of the potential project portfolios. A hybrid multi-objective framework integrates and synthesizes the results from a data mining model with the results from a Data Envelope Analysis (DEA) model and an Evolutionary Algorithm (EA) to design the structure of the proposed FRB system. The proposed framework simultaneously considers the accuracy maximization and the complexity minimization objectives. A Genetic Based Machine Learning (GBML) method is utilized to design an alternative FRB system for comparison purposes. The proposed framework and the GBML method are used to assess the alternative project portfolios in a real-world financial services institution. The statistical analysis shows the performance dominance of the proposed hybrid framework over the GBML method based on selected accuracy and interoperability measures.
Scientia Iranica
Project portfolio selection is an important problem for having an e cient and e ective project management. This paper proposes a new framework to identify the optimal project portfolio. First, the in uencing criteria are derived with respect to higher priorities from the fuzzy DEMATEL method under the balanced scorecard framework. Afterwards, a utility-based multi-choice goal programming technique is applied to determine the project portfolio in regard to the chosen criteria and some other operational limitations. The synergy amongst projects and the outsourcing option are also taken into account in order to provide a more realistic selection process. Finally, applicability and validity of the proposed integrated model are tested by a case study conducted in a pharmaceutical company.
Expert Systems with Applications, 2015
Project selection and resource allocation are critical issues in project-based organizations. These organizations are required to plan, evaluate, and control their projects in accordance with the organizational mission and objectives. In this study, we propose a three-stage hybrid method for selecting an optimal combination of projects. We obtain the maximum fitness between the final selection and the project initial rankings while considering various organizational objectives. The proposed model is comprised of three stages and each stage is composed of several steps and procedures. We use Data Envelopment Analysis (DEA) for the initial screening, the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) for ranking the projects, and linear Integer Programming (IP) for selecting the most suitable project portfolio in a fuzzy environment according to organizational objectives. Finally, a case study is used to demonstrate the applicability of the proposed method and exhibit the efficacy of the algorithms and procedures.
Application of Fuzzy Multi-Criteria Decision Making Methods on Six Sigma Projects Selection
2017
Six sigma method widely applied in production and service businesses is known as a project-oriented method. In six sigma method, selection of the prior project among others can be considered as a multi-criteria decision making problem. The conducted literature review has revealed that there is a large number of methods to select six sigma projects. It is more appropriate to use fuzzy multi-criteria decision making methods in project selection since evaluation criteria of six sigma projects include uncertainties. The aim of this study is to select the most appropriate project as a result of evaluating the projects by Fuzzy VIKOR, Fuzzy TOPSIS and Fuzzy COPRAS as methods of fuzzy multicriteria decision-making and integrating the ranking scores obtained from each method by Copeland method. The proposed method has been implemented in a large scale production company, operating in Aydın ASTİM Organized Industrial Zone. Highlights * The decision-making process has transformed to an even more complex structure from the existence of humankind to the present day because of the multiplicity of options. In this direction, integration with fuzzy logic in order to maximize the contributing elements of the multi-criteria decision making techniques further increases the efficiency further in decision making. These are included in the literature as "fuzzy multi-criteria decision making techniques" and have been used in many studies. * The purpose of this study was to select the most suitable project by using Copeland ordering method to integrate fuzzy VIKOR, fuzzy TOPSIS and fuzzy COPRAS methods, which are among the fuzzy multi-criteria decision making techniques, from six sigma projects. The evaluation of the projects could become possible with the aid of the criteria, which are the basis of the methods, and the weight of these criteria. In the literature, it is possible to find the studies that reveal the weights of criteria within the frame of fuzzy logic. In this study, the weights of the criteria were determined by using fuzzy AHP method and weights of the criteria obtained from the fuzzy AHP at the project evaluation stage were used in fuzzy VIKOR, fuzzy TOPSIS and fuzzy COPRAS. * Each project was evaluated by verbal variables by the decision makers also taking the criteria into consideration. Verbal variables belonging to each decision maker were transformed into fuzzy triangular numbers, and then merging operation was performed by considering decision maker weights to form a single decision matrix. Thus, a single fuzzy decision matrix of all decision makers was obtained. The combined fuzzy decision matrix was evaluated by fuzzy VIKOR, fuzzy TOPSIS and fuzzy COPRAS method, and project
Evaluating project management criteria using fuzzy analytic hierarchy Process
2019
Project management is one of the most important issues to fulfil organizational objectives. The project management criteria are playing a vital role for completion of any project. The aim of this paper is to evaluate five main project criteria (time, cost, quality, risk, and safety) mathematically by using a multi-criteria method in order to assist stakeholders or project managers in decision-making. The fuzzy Analytic Hierarchy Process (AHP) is selected with the use of triangular fuzzy numbers for pairwise comparison scales in prioritizing the criteria in managing projects. Utilizing the fuzzy AHP technique can facilitate uncertainty in doing evaluation. In this study, one expert who is a project manager with many years of experience was asked to carry out the evaluation. The results show that the expert’s main concern in managing project is time, and cost is the second important. The study demonstrates how uncertainty in making evaluation of multiple criteria can be solved by using fuzzy method such as fuzzy AHP, in contrary to the crisp or the traditional AHP which is based on specific values, the evaluator(s) are always ambiguous and vague to give exact judgment. Hence, the application of this fuzzy method can make the assessment outcomes more accurate, scientific, and objective. It is anticipated that this work may serve as a support tool for stakeholders in improving the project management quality level.
A multiobjective fuzzy model for selecting and planning a project portfolio in a public organisation
International Journal of Engineering Management and Economics, 2015
Our purpose in this paper is to assist decision-makers in the task of selecting project portfolios to satisfy their requirements and guarantee profitable growth. This task usually involves decision-makers having to face multiple objectives and constraints, as well as the uncertainty associated with certain parameters of the problem. Therefore, in this paper, we propose a multiobjective programming model, which includes uncertainty through the use A multiobjective fuzzy model for selecting and planning a project portfolio 49 of fuzzy parameters and allows us to represent information not fully known by the decision-makers. The resulting model has been applied to a project portfolio selection process in a public organisation.
Project portfolio selection: Multi-criteria analysis and interactions between projects
2015
In the project portfolio management, the project selection phase presents the greatest interest. In this article, we focus on this important phase by proposing a new method of projects selection consisting of several steps. We propose as a first step, a classification of projects based on the three most important criteria namely the value maximization, risk minimization and strategic alignment. The second step is building alternatives portfolio by the portfolio managers taking into account the classification of projects already completed in the first step. The third and final step enables the identification of the alternative portfolio to consider the contribution of projects to achieve the organization objectives as well as interactions between projects.