PEMODELAN PEMROGRAMAN LINIER DENGAN KOEFISIEN FUNGSI OBJEKTIF, FUNGSI KENDALA DAN VARIABEL KEPUTUSAN BERBENTUK BILANGAN KABUR BESERTA APLIKASINYA
DOI:
https://doi.org/10.20956/jmsk.v16i1.5802Keywords:
Fuzzy linier programming, rank function, simplex methodAbstract
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.
Abstract
In 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.
References
Asikin, M.,2003. Mencermati berbagai jenis permasalahan dalam program linear kabur, Jurnal matematika dan komputer, 2, 86-96.
Allahviranloo, T., 2009. Solving a fully fuzzy linear programming using lexicography method and fuzzy approximate solution, Appl. Math. Model. 33.
Ebrahimnejad, A., Nasseri, S. H., Lotfi F. H., dan Soltanifar, M., 2010. A primal-dual method for linear programming problems with fuzzy variables, Eur. J. Ind. Eng. 4, 189-209.
Hosseinzadeh, A., dan Edalatpanah, S. A., 2016. A new approach for solving fully fuzzy linear programming by using the lexicography method. Journal of fuzzy linear programming.
Kumar, A., Kaur, J., Singh, P., 2010. Fuzzy optimal solution of fully fuzzy linear programming problems with inequality constraints, International journal of applied mathematics and computer sciences 6, 37-41.
Kumar, A., dan Kaur, J., 2011. A new method for solving fuzzy linear programs with tapezoidal fuzzy numbers, Journal of fuzzy linear programming, Vol.102.
Kusumadewi., 2010. Aplikasi logika kabur untuk pendukung keputusan.
Yogyakarta: Graha Ilmu.
Maleki, H. R., 2002. Ranking functions and their applications to fuzzy linear programming, Journal of Fuzzy Linear Programming, Far East J. Appl. Math. 4, 283–301.
Nasseri, S.H., Ardil, E., Yazdani, A., dan Zaefarian, R., 2007. Simplex method for solving linear programming problems with fuzzy numbers, Journal of fuzzy linear programming, Vol:12, No.10, 2007.
Pandian, P., dan Jayalakshmi, M., 2010. A new for solving integer linear programming problems with fuzzy variabels, Applied mathematical sciences, vol : 4, No. 20, 997-1004.
Salim, R.dan Molani, M.,2014. Representation of trapezoidal fuzzy numbers with shape function, Annals of fuzzy mathematics and informatics, volume 8, No. 1.
Stanojevic, B. dan Stanojevic, M., 2009. Penalty method for fuzzy linear programming with trapezoidal numbers, Journal of operations research, 1, 149-156.
Wang, L.X., 1997. A course in fuzzy systems and control, prentice-hall Int., London.
Winston, W.L., 2003. Operations research: applications and algorithms, edisi-4, International Thomson Publishing, Belmont, California.
Zadeh, L.A.,1965. Fuzzy Set. Information and control, 8: 338-353. California.
Zimmermann, H.J., 1978. Fuzzy programming and linear programming with several objective functions, Fuzzy Sets and Systems.
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Jurnal Matematika, Statistika dan Komputasi is an Open Access journal, all articles are distributed under the terms of the Creative Commons Attribution License, allowing third parties to copy and redistribute the material in any medium or format, transform, and build upon the material, provided the original work is properly cited and states its license. This license allows authors and readers to use all articles, data sets, graphics and appendices in data mining applications, search engines, web sites, blogs and other platforms by providing appropriate reference.
