Abstract

In many real life optimization problems, the parameters are often imprecise and are difficult to be represented in discrete quantity. One of the approaches to model such situation is considering these imprecise parameters as intuitionistic fuzzy numbers and then approximating these by its expected interval value. Further in process of solution, membership function for each objective function are constructed by computing best and worst acceptable solutions and deal the constraints of the problem with ranking of intuitionistic fuzzy number with a concept of feasibility degree. The paper presents a computational algorithm for solution of objective functions at different feasibility degree. The developed algorithm has been illustrated by implementing on a linear programming problem as well as on a multi objective linear programming problem (MOLPP) in intuitionistic fuzzy environment.

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