On Inverse Linear Fractional Programming Problem

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 x0 is taken and have adjusted the model parameters as little as possible (under l1 or l2 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 is used for optimal solution. The method has been illustrated by a numerical example also.