APLIKASI PROGRAM LINEAR MULTIOBJEKTIF FUZZY PADA MASALAH PEMILIHAN SUPPLIER DAN PEMROGRAMAN KOMPUTERNYA
Supplier selection is a problem of selecting the right supplier and finding the right number of units will be purchased from selected supplier. In this thesis, supplier selection problem is defined as multiobjective linear programming. In real situation, decision maker does not have precise and cris...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Theses and Dissertations NonPeerReviewed |
| Published: |
[Yogyakarta] : Universitas Gadjah Mada
2011
|
| Subjects: | |
| Online Access: | https://repository.ugm.ac.id/90706/ http://etd.ugm.ac.id/index.php?mod=penelitian_detail&sub=PenelitianDetail&act=view&typ=html&buku_id=52433 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Universitas Gadjah Mada |
| Summary: | Supplier selection is a problem of selecting the right supplier and finding the
right number of units will be purchased from selected supplier. In this thesis,
supplier selection problem is defined as multiobjective linear programming. In
real situation, decision maker does not have precise and crisp information related
to the goals and the constraints. Fuzzy multiobjective linear programming is used
to overcome the imprecision of the information. In some cases, the goals and the
constraints have different importance to decision maker. To solve this problem we
use nonsymmetrical fuzzy decision on fuzzy multiobjective linear programming.
Fuzzy multiobjective linear programming is solved by transform it into
deterministic singleobjective linear programming, which can be solved using
Simplex method. To simplify it, linear programming software such as LINDO,
LINGO or �linprog� function in MATLAB can be used. The output is an optimal
solution which is also the optimal solution for fuzzy multiobjective linear
programming. Firstly, in this paper, we make a function in MATLAB, named
PLMOF, which can transform fuzzy multiobjective linear programming into
deterministic singleobjective linear programming, and get its optimal solution. At
the end of this thesis we present simulations using secondary data. |
|---|