Pareto-optimal solutions for multi-objective flexible linear programming
Copyright policy )Pareto-optimal solutions for multi-objective flexible linear programming
The aim of this paper is twofold. Firstly, to define a solution concept of Pareto-optimality for a multi-objective flexible linear programming (MOFLP) problem (or multi-objective fuzzy linear programming problem) and design a method to extract a Pareto-optimal solution of MOFLP problem from the set of optimal solutions of equivalent optimization problem formulated by Dubey and Mehra (2013). Secondly, to extend this study to multi-objective linear programming problem involving hard and flexible constraints with interval uncertainty. A flexible constraint with interval uncertainty generalizes a flexible constraint by allowing preferences to be expressed in the form of intervals. An optimistic-pessimistic approach is proposed to solve multi-objective flexible linear programming with interval uncertainty (MOFLPIU) using an interval-valued fuzzy set representation and the Hurwicz optimism-pessimism criterion.
fuzzy mathematical programming, Linear programming, flexible constraints, aggregation operator, Pareto-optimal solution, Fuzzy and other nonstochastic uncertainty mathematical programming, Multi-objective and goal programming, flexible constraint with interval uncertainty
fuzzy mathematical programming, Linear programming, flexible constraints, aggregation operator, Pareto-optimal solution, Fuzzy and other nonstochastic uncertainty mathematical programming, Multi-objective and goal programming, flexible constraint with interval uncertainty
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