Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Computation of mean-semivariance efficient sets by the Critical Line Algorithm
Annals of Operations Research
A model for portfolio selection with order of expected returns
Computers and Operations Research
Portfolio selection based on fuzzy probabilities and possibility distributions
Fuzzy Sets and Systems
Random fuzzy dependent-chance programming and its hybrid intelligent algorithm
Information Sciences—Informatics and Computer Science: An International Journal
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
Expected value operator of random fuzzy variable and random fuzzy expected value models
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Toward a generalized theory of uncertainty (GTU): an outline
Information Sciences—Informatics and Computer Science: An International Journal
A survey of credibility theory
Fuzzy Optimization and Decision Making
Optimal consumption and portfolio choice with ambiguity and anticipation
Information Sciences: an International Journal
Risk curve and fuzzy portfolio selection
Computers & Mathematics with Applications
Portfolio selection with fuzzy returns
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
A stochastic soft constraints fuzzy model for a portfolio selection problem
Fuzzy Sets and Systems
IEEE Transactions on Fuzzy Systems
Expected value of fuzzy variable and fuzzy expected value models
IEEE Transactions on Fuzzy Systems
Random fuzzy programming with chance measures defined by fuzzy integrals
Mathematical and Computer Modelling: An International Journal
Information Sciences: an International Journal
Pricing a contingent claim with random interval or fuzzy random payoff in one-period setting
Computers & Mathematics with Applications
Fuzzy portfolio selection using fuzzy analytic hierarchy process
Information Sciences: an International Journal
Modelling redundancy allocation for a fuzzy random parallel-series system
Journal of Computational and Applied Mathematics
A review of credibilistic portfolio selection
Fuzzy Optimization and Decision Making
Information Sciences: an International Journal
Application of fuzzy calculations for improving portfolio matrices
Information Sciences: an International Journal
A hybrid approach to asset allocation with simultaneous consideration of suitability and optimality
Information Sciences: an International Journal
Two-stage fuzzy stochastic programming with Value-at-Risk criteria
Applied Soft Computing
A hybrid approach for constructing suitable and optimal portfolios
Expert Systems with Applications: An International Journal
A multi-objective genetic algorithm for cardinality constrained fuzzy portfolio selection
Fuzzy Sets and Systems
A portfolio selection model with borrowing constraint based on possibility theory
Applied Soft Computing
Selection of Socially Responsible Portfolios using Goal Programming and fuzzy technology
Information Sciences: an International Journal
A fuzzy multi-objective approach for sustainable investments
Expert Systems with Applications: An International Journal
PB-ADVISOR: A private banking multi-investment portfolio advisor
Information Sciences: an International Journal
Information Sciences: an International Journal
Gradually tolerant constraint method for fuzzy portfolio based on possibility theory
Information Sciences: an International Journal
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The aim of this paper is to solve the portfolio selection problem when security returns contain both randomness and fuzziness. Utilizing a different perspective, this paper gives a new definition of risk for random fuzzy portfolio selection. A new optimal portfolio selection model is proposed based on this new definition of risk. A new hybrid intelligent algorithm is designed for solving the new optimization problem. In the proposed new algorithm, neural networks are employed to calculate the expected value and the chance value. These greatly reduce the computational work and speed up the process of solution as compared with the random fuzzy simulation used in our previous algorithm. A numerical example is also presented to illustrate the new modelling idea and the proposed new algorithm.