Mean lower partial moment valuation and lognormally distributed returns
Management Science
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
The expected value of a fuzzy number
Fuzzy Sets and Systems
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Annals of Operations Research
Genetic programming II (videotape): the next generation
Genetic programming II (videotape): the next generation
Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Genetic algorithms + data structures = evolution programs (3rd ed.)
Genetic algorithms + data structures = evolution programs (3rd ed.)
Portfolio selection based on fuzzy probabilities and possibility distributions
Fuzzy Sets and Systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms
Theory and Practice of Uncertain Programming
Theory and Practice of Uncertain Programming
A possibilistic approach to selecting portfolios with highest utility score
Fuzzy Sets and Systems - Special issue: Soft decision analysis
Portfolio selection with fuzzy returns
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Expected value of fuzzy variable and fuzzy expected value models
IEEE Transactions on Fuzzy Systems
Risk curve and fuzzy portfolio selection
Computers & Mathematics with Applications
Portfolio selection based on fuzzy cross-entropy
Journal of Computational and Applied Mathematics
A hybrid intelligent algorithm for portfolio selection problem with fuzzy returns
Journal of Computational and Applied Mathematics
A review of credibilistic portfolio selection
Fuzzy Optimization and Decision Making
Mean-Entropy-Skewness Fuzzy Portfolio Selection by Credibility Theory Approach
PReMI '09 Proceedings of the 3rd International Conference on Pattern Recognition and Machine Intelligence
PSO-based possibilistc mean-variance model with transaction costs
CCDC'09 Proceedings of the 21st annual international conference on Chinese control and decision conference
Fuzzy multi-objective portfolio selection model with transaction costs
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Possibilistic mean value and variance of fuzzy numbers: some examples of application
FUZZ-IEEE'09 Proceedings of the 18th international conference on Fuzzy Systems
Portfolio adjusting optimization under credibility measures
Journal of Computational and Applied Mathematics
Fuzzy mean-variance-skewness portfolio selection models by interval analysis
Computers & Mathematics with Applications
Computers and Industrial Engineering
A new MOPSO to solve a multi-objective portfolio selection model with fuzzy value-at-risk
KES'11 Proceedings of the 15th international conference on Knowledge-based and intelligent information and engineering systems - Volume Part III
Mean-risk model for hybrid portfolio selection with fuzziness and randomness
ICHIT'11 Proceedings of the 5th international conference on Convergence and hybrid information technology
Mean-variance models for portfolio selection subject to experts' estimations
Expert Systems with Applications: An International Journal
PB-ADVISOR: A private banking multi-investment portfolio advisor
Information Sciences: an International Journal
A risk index model for multi-period uncertain portfolio selection
Information Sciences: an International Journal
A risk index model for portfolio selection with returns subject to experts' estimations
Fuzzy Optimization and Decision Making
| Hi-index | 7.30 |
This paper discusses portfolio selection problem in fuzzy environment. In the paper, semivariance is originally presented for fuzzy variable, and three properties of the semivariance are proven. Based on the concept of semivariance of fuzzy variable, two fuzzy mean-semivariance models are proposed. To solve the new models in general cases, a fuzzy simulation based genetic algorithm is presented in the paper. In addition, two numerical examples are also presented to illustrate the modelling idea and the effectiveness of the designed algorithm.