Multiple objective programming problems with possibilistic coefficients
Fuzzy Sets and Systems
Linear programming with fuzzy random variable coefficients
Fuzzy Sets and Systems
Challenges in stochastic programming
Mathematical Programming: Series A and B
Fuzzy programming approach to multi-objective stochastic linear programming problems
Fuzzy Sets and Systems
Chance constrained programming with fuzzy parameters
Fuzzy Sets and Systems
Stochastic vs. Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty
Stochastic vs. Fuzzy Approaches to Multiobjective Mathematical Programming under Uncertainty
A Possibilistic and Stochastic Programming Approach to Fuzzy Random MST Problems*
IEICE - Transactions on Information and Systems
Personal financial planning based on fuzzy multiple objective programming
Expert Systems with Applications: An International Journal
Expert Systems with Applications: An International Journal
A random fuzzy minimum spanning tree problem through a possibility-based value at risk model
Expert Systems with Applications: An International Journal
Hi-index | 12.05 |
In this paper, we focus on multiobjective integer programming problems involving random variable coefficients in objective functions and constraints. Using the concept of chance constrained conditions, such multiobjective stochastic integer programming problems are transformed into deterministic ones based on the fractile criterion optimization model. As a fusion of stochastic programming and fuzzy one, we introduce fuzzy goals representing the ambiguity of the decision maker's judgments into them and define M-@q-efficiency, a new concept of efficient solution, as a fusion of stochastic approaches and fuzzy ones. Then, we construct an interactive fuzzy satisficing method using genetic algorithms to derive a satisficing solution for the decision maker which is guaranteed to be M-@q-efficient by updating the reference membership levels. Finally, the efficiency of the proposed method is demonstrated through numerical experiments.