Kajian Penerapan Program Linear Multi Objektif Fuzzy Interaktif Pada Keputusan Perencanaan Transportasi

In this paper, we discusses the problem that involving the conflict fuzzy multi-objective in transportation planning which is one of special case in multi-objective linear programming. To find the simultaneously optimal solution of the problem, we use the Interactive Fuzzy Multi-Objective Linear Programming (IFMOLP) method. This method can reduce the fuzzy multi-objective linear programming problem into deterministic single objective linear programming which can be solved using simplex method. Beside that , with IFMOLP method, decision maker (DM) can establish interactively the goal from the objective function to produce the pareto optimal solution so that

An iterative approach for fuzzy multi objective linear fractional programming problem

In this paper, we introduce an iterative method for the solution of fully fuzzy single and multi objective linear fractional programming problems with out converting them into equivalent crisp forms. By introducing fuzzy target and the fuzzy tolerance limit for each objective of the given fuzzy multi objective linear fractional programming problem (FMOLFPP), the given FMOLFPP is reduced to an equivalent single objective non-fractional fuzzy linear programming problem (NFLPP). Then the fuzzy optimal solution of the reduced NFLPP is obtained which inturn provides the Pareto optimal solution of the given FMOLFPP. Numerical examples are provided to illustrate the efficiency of the proposed method.Publisher's Versio

Program Linier Fuzzy Penuh Dengan Algoritma Multi Objective Linear Programming

In the linear programming there is one of the certainty assumptions, where each parameters has been known with certainty, but in this real life, the parameters is often can not be stated with certainty, so that the linear programming developed into fully fuzzy linear programming (FFLP). This paper discusses the problem solving FFLP problem with Multi Objective Linear Programming Algorithm. FFLP problem will be converted to MOLP problem with three objective functions by using a new lexicographic ordering on triangular fuzzy numbers and then it is solved by lexicographic method. The value of the fuzzy optimal solution obtained is used to find the optimal value of fuzzy objective function and then do defuzzification to obtain crisp optimal solution

Program Linier Fuzzy Penuh Dengan Algoritma Multi Objective Linear Programming Menggunakan Metode Level Sum

. Fully Fuzzy Linear Programming (FFLP) is one form of fuzzy linear program that the decision variables, limiting the mark, the objective function coefficients, the coefficient constraints and right hand side constraints are fuzzy numbers. Fuzzy numbers used in FFLP is triangular fuzzy numbers.Several methods have been developed to solve FFLP one method Kumar. This thesis explores the completion FFLP with multi-objective algorithm linear programming (MOLP) and compared with the method of Kumar. FFLP problem will be transformed into a problem MOLP with triangular fuzzy numbers and then completed Level Sum Method

Fuzzy Multi-objective Linear Programming Approach

Traveling salesman problem (TSP) is one of the challenging real-life problems, attracting researchers of many fields including Artificial Intelligence, Operations Research, and Algorithm Design and Analysis. The problem has been well studied till now under different headings and has been solved with different approaches including genetic algorithms and linear programming. Conventional linear programming is designed to deal with crisp parameters, but information about real life systems is often available in the form of vague descriptions. Fuzzy methods are designed to handle vague terms, and are most suited to finding optimal solutions to problems with vague parameters. Fuzzy multi-objective linear programming, an amalgamation of fuzzy logic and multi-objective linear programming, deals with flexible aspiration levels or goals and fuzzy constraints with acceptable deviations. In this paper, a methodology, for solving a TSP with imprecise parameters, is deployed using fuzzy multi-objective linear programming. An example of TSP with multiple objectives and vague parameters is discussed

Multi-level Multi-objective Quadratic Fractional Programming Problem with Fuzzy Parameters: A FGP Approach

The motivation behind this paper is to present multi-level multi-objective quadratic fractional programming (ML-MOQFP) problem with fuzzy parameters in the constraints. ML-MOQFP problem is an important class of non-linear fractional programming problem. These type of problems arise in many fields such as production planning, financial and corporative planning, health care and hospital planning. Firstly, the concept of the -cut and fuzzy partial order relation are applied to transform the set of fuzzy constraints into a common crisp set. Then, the quadratic fractional objective functions in each level are transformed into non-linear objective functions based on a proposed transformation. Secondly, in the proposed model, separate non-linear membership functions for each objective function of the ML-MOQFP problem are defined. Then, the fuzzy goal programming (FGP) approach is utilized to obtain a compromise solution for the ML-MOQFP problem by minimizing the sum of the negative deviational variables. Finally, an illustrative numerical example is given to demonstrate the applicability and performance of the proposed approach

Penalty method for fuzzy linear programming with trapezoidal numbers

In this paper we shall propose an algorithm for solving fuzzy linear programming problems with trapezoidal numbers using a penalty method. We will transform the problem of maximizing a function having trapezoidal fuzzy number values under some constraints into a deterministic multi-objective programming problem by penalizing the objective function for possible constraint violation. Furthermore, the obtained deterministic problem will have only unavoidable inequalities between trapezoidal fuzzy numbers parameters as constraints

Comparative Evaluation of the Performance of Spans of Control Designs in Grain Supply Chains

A fuzzy multi-objective linear programming model is used to analyze the performances of three spans of control designs that are observed in the U.S grain industry. Performance of the grain supply chain increases with amount of control and compromise.Crop Production/Industries,

A fuzzy goal programming approach to solving decentralized bi-level multi-objective linear fractional programming problems

This paper presents a new approach for solving decentralized bi-level multi-objective linear fractional programming problems. The main goal was to find a simple algorithm with high confidence of decision-makers in the results. First, all the linear fractional programming models on the given set of constraints were solved separately. Next, all the linear fractional objective functions were linearized, membership functions of objective functions and decision variables controlled by decision-makers at the highest level calculated, and a fuzzy multi-objective linear programming model formed and solved as linear goal programming problem by using simplex algorithm. The efficiency of the proposed algorithm was investigated using an economic example, and the obtained results compared with those obtained using an existing method

Analysis of Grain Supply Chain Performance Based on Relative Impact of Channel Coordinator's Objectives on Firm Level Objectives

A fuzzy multi-objective programming model is used to analyze the optimal decisions in a multi-objective grain supply chain in which the firm-level firm goals are conflicting with the channel coordinator's goals. The relative impact of the channel coordinator's goals on performance of the supply chain is determined through a linear weighting method. The study finds that prioritizing the channel coordinator's goals enhances the overall performance of the system.Industrial Organization,