A Hybrid Grey Based KOHONEN Model and Biogeography-Based Optimization for Project Portfolio Selection
The problem of selection and the best option are the main subject of operation research science in decision-making theory. Selection is a process that scrutinizes and investigates several quantitative and qualitative, and most often incompatible, factors. One of the most fundamental management issue...
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| Vydáno v: | Journal of Applied Mathematics Ročník 2014; číslo 2014; s. 759 - 770-067 |
|---|---|
| Hlavní autoři: | , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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Cairo, Egypt
Hindawi Limiteds
01.01.2014
Hindawi Puplishing Corporation Hindawi Publishing Corporation John Wiley & Sons, Inc Wiley |
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| ISSN: | 1110-757X, 1687-0042 |
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| Abstract | The problem of selection and the best option are the main subject of operation research science in decision-making theory. Selection is a process that scrutinizes and investigates several quantitative and qualitative, and most often incompatible, factors. One of the most fundamental management issues in multicriteria selection literature is the multicriteria adoption of the projects portfolio. In such decision-making condition, manager is seeking for the best combination to build up a portfolio among the existing projects. In the present paper, KOHONEN algorithm was first employed to build up a portfolio of the projects. Next, each portfolio was evaluated using grey relational analysis (GRA) and then scheduled risk of the project was predicted using Mamdani fuzzy inference method. Finally, the multiobjective biogeography-based optimization algorithm was utilized for drawing risk and rank Pareto analysis. A case study is used concurrently to show the efficiency of the proposed model. |
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| AbstractList | The problem of selection and the best option are the main subject of operation research science in decision-making theory. Selection is a process that scrutinizes and investigates several quantitative and qualitative, and most often incompatible, factors. One of the most fundamental management issues in multicriteria selection literature is the multicriteria adoption of the projects portfolio. In such decision-making condition, manager is seeking for the best combination to build up a portfolio among the existing projects. In the present paper, KOHONEN algorithm was first employed to build up a portfolio of the projects. Next, each portfolio was evaluated using grey relational analysis (GRA) and then scheduled risk of the project was predicted using Mamdani fuzzy inference method. Finally, the multiobjective biogeography-based optimization algorithm was utilized for drawing risk and rank Pareto analysis. A case study is used concurrently to show the efficiency of the proposed model. |
| Audience | Academic |
| Author | Faezy Razi, Farshad Alborzi, Mahmood Pourebrahimi, Alireza Eshlaghy, Abbas Toloie Nazemi, Jamshid |
| Author_xml | – sequence: 1 fullname: Alborzi, Mahmood – sequence: 2 fullname: Eshlaghy, Abbas Toloie – sequence: 3 fullname: Nazemi, Jamshid – sequence: 4 fullname: Pourebrahimi, Alireza – sequence: 5 fullname: Faezy Razi, Farshad |
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| Contributor | Faezy Razi, Farshad Alborzi, Mahmood Pourebrahimi, Alireza Eshlaghy, Abbas Toloie Nazemi, Jamshid |
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| Copyright | Copyright © 2014 Farshad Faezy Razi et al. COPYRIGHT 2014 John Wiley & Sons, Inc. Copyright © 2014 Farshad Faezy Razi et al. Farshad Faezy Razi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Copyright 2014 Hindawi Publishing Corporation |
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| SubjectTerms | Accumulation Algorithms Analysis Biogeography Case studies Data mining Decision making Decision theory Fuzzy Fuzzy logic Industrial project management Integer programming Mathematical models Monte Carlo simulation Neural networks Optimization Pareto analysis Project management R&D Research & development Studies |
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| Title | A Hybrid Grey Based KOHONEN Model and Biogeography-Based Optimization for Project Portfolio Selection |
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