A Goal Programming Procedure for Solving Interval Valued Multiobjective Fractional Programming Problems

This article presents a goal programming (GP) procedure for solving interval valued multiobjective fractional programming problems (MOFPPs) with interval objective functions in an inexact environment. In the proposed approach, the interval objective functions are first converted into the standard objective goals in the fractional GP formulation by using the interval arithmetic technique. Then, in the decision process, the fractional goals are transformed into the linear goals by linearization approach by B.B. Pal et al (2008) studied previously. In solution process, the executable GP model of the problem is formulated with the objective to minimize the regret with the view to achieve the goals in their specified ranges and thereby arriving at a most satisfactory solution in the decision making environment. Two numerical examples are solved to illustrate the proposed approach and the model solution of one problem is compared with the solution of a fuzzy programming approach by B.B. Pal et al. (2008) studied previously.