About One Inverse Problem of the Linear-Fractional Programming on Generalized Network

Abstract

For the one linear-fractional network programming problem with additional constraints of general kind and with inexact data we constructed a mathematical model for calculation of the new parameters of the restrictions for which the infeasible solution becomes feasible solution. or the selected feasible solution of this problem we minimally changed the parameters in the numerator of the linear-fractional objective function in order that the selected feasible solution has become an optimal. The measure proximity vectors estimated are using the norm l1. That has allowed to remain within the framework of linear programming in solving of inverse problems.