Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Genetic algorithms + data structures = evolution programs (2nd, extended ed.)
Fuzzy Sets and Systems - Fuzzy mathematical programming
Portfolio selection based on fuzzy probabilities and possibility distributions
Fuzzy Sets and Systems
Portfolio selection under independent possibilistic information
Fuzzy Sets and Systems - Special issue on soft decision analysis
Heuristics for cardinality constrained portfolio optimisation
Computers and Operations Research
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms and Manufacturing Systems Design
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
Theory and Practice of Uncertain Programming
Theory and Practice of Uncertain Programming
A class of linear interval programming problems and its application to portfolio selection
IEEE Transactions on Fuzzy Systems
A portfolio selection model using fuzzy returns
Fuzzy Optimization and Decision Making
Robust-based interactive portfolio selection problems with an uncertainty set of returns
Fuzzy Optimization and Decision Making
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Because of the existence of non-stochastic factors in stock markets, several possibilistic portfolio selection models have been proposed, where the expected return rates of securities are considered as fuzzy variables with possibilistic distributions. This paper deals with a possibilistic portfolio selection model with interval center values. By using modality approach and goal attainment approach, it is converted into a nonlinear goal programming problem. Moreover, a genetic algorithm is designed to obtain a satisfactory solution to the possibilistic portfolio selection model under complicated constraints. Finally, a numerical example based on real world data is also provided to illustrate the effectiveness of the genetic algorithm.