We focus on multiobjective linear fractional programming problems with fuzzy parameters and extend the ordinary Pareto optimality concepts based on the concepts of possibility and necessity for fuzzy numbers. Using the four indices for ranking two fuzzy numbers, four types of Pareto optimality are defined, and the relationships among them are examined in detail. These concepts can be viewed as quite generalized versions of the well-known Pareto optimality concepts, and the generalized Pareto optimal solutions for the multiobjective linear fractional programming problems with fuzzy parameters may be obtained on the basis of the simplex method of linear programming.
ASJC Scopus subject areas
- Control and Systems Engineering
- Theoretical Computer Science
- Computer Science Applications
- Information Systems and Management
- Artificial Intelligence