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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Veröffentlicht in:Journal of Applied Mathematics Jg. 2014; H. 2014; S. 759 - 770-067
Hauptverfasser: Alborzi, Mahmood, Eshlaghy, Abbas Toloie, Nazemi, Jamshid, Pourebrahimi, Alireza, Faezy Razi, Farshad
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Cairo, Egypt Hindawi Limiteds 01.01.2014
Hindawi Puplishing Corporation
Hindawi Publishing Corporation
John Wiley & Sons, Inc
Wiley
Schlagworte:
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
ISSN:1110-757X, 1687-0042
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Beschreibung
Zusammenfassung: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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ISSN:1110-757X
1687-0042
DOI:10.1155/2014/159675