a method for solving possibilistic multi-objective linear programming problems with fuzzy decision variables

Authors

مهناز حسین زاده

دکتری مدیریت تحقیق در عملیات، دانشکدة مدیریت دانشگاه تهران، تهران، ایران محمدباقر منهاج

استاد دانشکدة مهندسی برق و الکترونیک، دانشگاه امیرکبیر، تهران، ایران عالیه کاظمی

استادیار دانشکدة مدیریت دانشگاه تهران، تهران، ایران

abstract

[naeini1] in this paper, a new method is proposed to find the fuzzy optimal solution of fuzzy multi-objective linear programming problems (fmolpp) with fuzzy right hand side and fuzzy decision variables. due to the imprecise nature of available resources, determination of a definitive solution to the model seems impossible. therefore, the proposed model is designed in order to make fuzzy decisions. the model resolves the deficiencies of the previous models presented in this field and its main advantage is simplicity. to illustrate the efficiency of the proposed method, it is applied to the problem of allocating orders to suppliers. due to the nature of the fuzzy solutions obtained from solving the model, the decision maker will be faced with more flexibility in decision making.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

A new method for solving fuzzy multi-objective linear programming problems

The purpose of this paper is to develop a new two-stage method for fuzzy multi-objective linear program and apply to engineering project portfolio selection. In the fuzzy multi-objective linear program, all the objective coefficients, technological coefficients and resources are trapezoidal fuzzy numbers (TrFNs). An order relationship for TrFNs is introduced by using the interval expectation of...

full text

On solving possibilistic multi- objective De Novo linear programming

Multi-objective De Novo linear programming (MODNLP) is problem for designing optimal system by reshaping the feasible set (Fiala [3] ). This paper deals with MODNLP having possibilistic objective functions coefficients. The problem is considered by inserting possibilistic data in the objective functions coefficients. The solution of the problem is defined and established under the using of effi...

full text

Providing a Method for Solving Interval Linear Multi-Objective Problems Based on the Goal Programming Approach

Most research has focused on multi-objective issues in its definitive form, with decision-making coefficients and variables assumed to be objective and constraint functions. In fact, due to inaccurate and ambiguous information, it is difficult to accurately identify the values of the coefficients and variables. Interval arithmetic is appropriate for describing and solving uncertainty and inaccu...

full text

Defuzzification Method for Solving ‎Fuzzy ‎Linear Programming Problems

Several authors have proposed different methods to find the solution of fully fuzzy linear programming (FFLP) problems. But all the existing methods are based on the assumption that all the fuzzy coefficients and the fuzzy variables are non-negative fuzzy numbers. in this paper a new method is proposed to solve an FFLP problems with arbitrary fuzzy coefficients and arbitrary fuzzy variables, th...

full text

A New Method For Solving Linear Bilevel Multi-Objective Multi-Follower Programming Problem

Linear bilevel programming is a decision making problem with a two-level decentralized organization. The leader is in the upper level and the follower, in the lower level. This study addresses linear bilevel multi-objective multi-follower programming (LB-MOMFP) problem, a special case of linear bilevel programming problems with one leader and multiple followers where each decision maker has sev...

full text

SOLVING FUZZY LINEAR PROGRAMMING PROBLEMS WITH LINEAR MEMBERSHIP FUNCTIONS-REVISITED

Recently, Gasimov and Yenilmez proposed an approach for solving two kinds of fuzzy linear programming (FLP) problems. Through the approach, each FLP problem is first defuzzified into an equivalent crisp problem which is non-linear and even non-convex. Then, the crisp problem is solved by the use of the modified subgradient method. In this paper we will have another look at the earlier defuzzifi...

full text

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023