A branch and bound algorithm for the bilevel programming problem
SIAM Journal on Scientific and Statistical Computing
New branch-and-bound rules for linear bilevel programming
SIAM Journal on Scientific and Statistical Computing
Linear programming with fuzzy random variable coefficients
Fuzzy Sets and Systems
Stackelberg solutions to multiobjective two-level linear programming problems
Journal of Optimization Theory and Applications
Genetic Algorithms and Fuzzy Multiobjective Optimization
Genetic Algorithms and Fuzzy Multiobjective Optimization
Random fuzzy dependent-chance programming and its hybrid intelligent algorithm
Information Sciences—Informatics and Computer Science: An International Journal
Global Optimization of Nonlinear Bilevel Programming Problems
Journal of Global Optimization
A Trust-Region Method for Nonlinear Bilevel Programming: Algorithm and Computational Experience
Computational Optimization and Applications
Parametric global optimisation for bilevel programming
Journal of Global Optimization
Bilevel optimization applied to strategic pricing in competitive electricity markets
Computational Optimization and Applications
Fuzzy Stochastic Multiobjective Programming
Fuzzy Stochastic Multiobjective Programming
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This paper considers computational methods for obtaining Stackelberg solutions to random fuzzy two-level linear programming problems. Assuming that the decision makers concerns about the probabilities that their own objective function values are smaller than or equal to certain target values, fuzzy goals of the decision makers for the probabilities are introduced. Using the possibility-based probability model to maximize the degrees of possibility with respect to the attained probability, the original random fuzzy two-level programming problems are reduced to deterministic ones. Extended concepts of Stackelberg solutions are introduced and computational methods are also presented. A numerical example is provided to illustrate the proposed method.