On Inverse Linear Fractional Programming Problem

Abstract

In this paper, we have proposed an inverse model for linear fractional programming (LFP) problems, in which the cost coefficients, technical coefficients and right hand side vector are adjusted as little as possible so that the given feasible or infeasible solution becomes optimal. In our proposed
method, a nonnegative solution x^0 is taken and have adjusted the model parameters as little as possible (under l_1 or l_2 measure) by taking following cases (i) adjusting cost coefficients (ii) adjusting cost, constraint coefficients and right hand side vector (iii) adjusting cost and constraint coefficients (iv) adjusting cost and right hand side vector. Complementary slackness conditions along with some standard transformations and MATLAB