A study on linear fractional programming problems in fuzzy environment

Abstract

Operations Research is a noteworthy arithmetical mechanism to augment the competence of executive decisions Linear Programming is a technique for determining an optimum schedule of interdependent activities in view of the existing resources Fractional Programming is an optimization technique used in decision making procedure Linear fractional programming is a particular case of fractional programming which optimizes the fraction of two linear functions subject to a certain set of constraints The constraints are in the structure of linear inequalities Plentiful factors in organization sciences provide mount to fractional programming problem Factual being situations are frequently not sure but require to be modeled by means of fuzzy coefficients This thesis aims at studying various methods of solving linear fractional programming problems in fuzzy environment The objective function of the linear fractional programming problem can be converted into inequality constraints The system of linear inequalities is solved by Fourier Motzkin Elimination method In this method the variables are eliminated one by one and the optimal solution is obtained by backward substitution method The parameters of the problem are specified as trapezoidal fuzzy numbers newline