Proceedings of the International Conference on Science and Technology (ICST 2018)

Multi-objective Linear Programming for Supplier Selection and Order Allocation of Raw Material

Authors
Ika Deefi Anna
Corresponding Author
Ika Deefi Anna
Available Online December 2018.
DOI
https://doi.org/10.2991/icst-18.2018.144How to use a DOI?
Keywords
multi-objective linear programming; supplier selection; order allocation
Abstract
The production process of a company is very dependent on the availability of raw materials. Raw materials will be available if there are suppliers who send raw materials continuously to the company. As we know that each supplier has difference in price, supply capacity, delivery time and quality of raw materials. Therefore, determining the right supplier is the important process in maintaining company production process. The objective of this study is to select the supplier and allocate orders to the selected supplier by developing the multi-objective linear programming (MOLP). The developed MOLP model will minimize 3 objective functions which include total cost, number of defective raw materials and total delivery time. Numerical examples is provided in this study for application the proposed model. The obtained results prove that the developed model has a better ability to select supplier and allocate the orders to the selected supplier.
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This is an open access article distributed under the CC BY-NC license.

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Volume Title
Proceedings of the International Conference on Science and Technology (ICST 2018)
Series
Atlantis Highlights in Engineering
Publication Date
December 2018
ISBN
978-94-6252-650-1
ISSN
2589-4943
DOI
https://doi.org/10.2991/icst-18.2018.144How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Ika Deefi Anna
PY  - 2018/12
DA  - 2018/12
TI  - Multi-objective Linear Programming for Supplier Selection and Order Allocation of Raw Material
BT  - Proceedings of the International Conference on Science and Technology (ICST 2018)
PB  - Atlantis Press
SP  - 710
EP  - 714
SN  - 2589-4943
UR  - https://doi.org/10.2991/icst-18.2018.144
DO  - https://doi.org/10.2991/icst-18.2018.144
ID  - Anna2018/12
ER  -