scholarly journals PEMODELAN PEMROGRAMAN LINIER DENGAN KOEFISIEN FUNGSI OBJEKTIF, FUNGSI KENDALA DAN VARIABEL KEPUTUSAN BERBENTUK BILANGAN KABUR BESERTA APLIKASINYA

2019 ◽  
Vol 16 (1) ◽  
pp. 85
Author(s):  
Muhammad Amrullah
Keyword(s):  
Decision Making ◽  
Linear Programming ◽  
Simplex Method ◽  
Fuzzy Linear Programming ◽  
Rank Function ◽  
New Method ◽  
Linear Programming Problems ◽  
Paper Author

Abstrak Dalam penelitian ini penulis akan mengusulkan algoritma untuk memodelkan masalah pemrograman linear kabur dengan bilangan kabur trapesium menggunakan metode simpleks. Secara khusus dalam aplikasi teori ini adalah masalah pengambilan keputusan pemrograman linear kabur dengan menyajikan metode baru untuk menyelesaikan masalah pemrograman linier kabur dengan menggunakan fungsi ranking. Pada dasarnya, langkah-langkah dalam metode penelitian ini sama dengan dengan metode simpleks yang digunakan untuk memecahkan masalah pemrograman linier tegas.Kata kunci: Fuzzy linear programming, fungsi ranking, metode simpleks. AbstractIn this paper author shall propose an algorithm for solving fuzzy linear programming problems with trapezoidal numbers using a simplex method. In particular, an application of  this theory in decision making problems is fuzzy linear programming with a new method for solving fuzzy linear programming problems, by use of rank function. Basically, our method is similar to simplex method that was used for solving linear programming problems in crisp environment before.Keywords: Fuzzy linier programming, rank function, simplex method.

Reduction-by-Projection Method for Linear Programming Problems

2014 ◽  
Vol 672-674 ◽  
pp. 1968-1971
Author(s):  
Xue Tong ◽  
Jun Qiang Wei
Keyword(s):  
Linear Programming ◽  
Linear Systems ◽  
Integer Linear Programming ◽  
Projection Method ◽  
Simplex Method ◽  
New Method ◽  
Linear Programming Problems

This paper defines the projection of algebic systems, and studies the projecting algorithm for linear systems. As its application, a new method is given to solve linear programming problems, which is called reduction-by-projection method. For many problems, especially when the problems have many constraint conditions in comparison with the number of their variables, the method needs less computation than simplex method and others. The great advantage of the method is shown when solving the integer linear programming problems.

scholarly journals A new method for solving fully fuzzy linear programming problems

2011 ◽  
Vol 35 (2) ◽  
pp. 817-823 ◽  
Author(s):  
Amit Kumar ◽  
Jagdeep Kaur ◽  
Pushpinder Singh
Keyword(s):  
Linear Programming ◽  
Fuzzy Linear Programming ◽  
New Method ◽  
Linear Programming Problems

scholarly journals Sensitivity Analysis for Interval-valued Fully Fuzzy Linear Programming Problems

2012 ◽  
Vol 10 (6) ◽  
Author(s):  
Neha Bhatia ◽  
Amit Kumar
Keyword(s):  
Sensitivity Analysis ◽  
Linear Programming ◽  
Fuzzy Numbers ◽  
Fuzzy Linear Programming ◽  
New Method ◽  
Trapezoidal Fuzzy Numbers ◽  
Linear Programming Problems ◽  
Interval Valued

In previous studies, it is pointed out that in several situations it is better to use interval-valued fuzzy numbers insteadof triangular or trapezoidal fuzzy numbers. But till now, there is no method that deals with the sensitivity analysis ofsuch linear programming problems in which all the parameters are represented by interval-valued fuzzy numbers. Inthis paper, a new method is proposed for the sensitivity analysis. Finally, the proposed method is illustrated using anumerical example.

scholarly journals Interior Point Method for Solving Fuzzy Number Linear Programming Problems Using Linear Ranking Function

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Yi-hua Zhong ◽  
Yan-lin Jia ◽  
Dandan Chen ◽  
Yan Yang
Keyword(s):  
Linear Programming ◽  
Interior Point ◽  
Fuzzy Number ◽  
Simplex Method ◽  
Interior Point Method ◽  
Large Scale ◽  
Ranking Function ◽  
Point Method ◽  
Fuzzy Linear Programming ◽  
Linear Programming Problems

Recently, various methods have been developed for solving linear programming problems with fuzzy number, such as simplex method and dual simplex method. But their computational complexities are exponential, which is not satisfactory for solving large-scale fuzzy linear programming problems, especially in the engineering field. A new method which can solve large-scale fuzzy number linear programming problems is presented in this paper, which is named a revised interior point method. Its idea is similar to that of interior point method used for solving linear programming problems in crisp environment before, but its feasible direction and step size are chosen by using trapezoidal fuzzy numbers, linear ranking function, fuzzy vector, and their operations, and its end condition is involved in linear ranking function. Their correctness and rationality are proved. Moreover, choice of the initial interior point and some factors influencing the results of this method are also discussed and analyzed. The result of algorithm analysis and example study that shows proper safety factor parameter, accuracy parameter, and initial interior point of this method may reduce iterations and they can be selected easily according to the actual needs. Finally, the method proposed in this paper is an alternative method for solving fuzzy number linear programming problems.

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