Application of linear programming in production planning

Oluwasegun Solaja, Joachim Abolaji Abiodun, Matthew Adekunle Abioro, Jonathan Ehimen Ekpudu and Olajide Moses Olasubulumi

MPRA Paper from University Library of Munich, Germany

Abstract: Optimum utilization of limited resources in the production floor demands that the production manager makes decisions on the best allocation of limited resources. Linear programming techniques are applied in this study to a production planning problem in a feed mill producing company. The linear Programming model was formulated based on data obtained from the company operations’ diary. Data was processed with the help of Management Scientist Version 5.0. The study reveals improved profit through streamlining of the product range and cutting off the less productive products. This suggests the company may adopt the outcome of the linear programming techniques in production planning to improve monthly profit. This study has shown that linear programming techniques are powerful tools that can be of help to managers in decision making and allocation of limited resources and indicate operations and profit improvement.

Keywords: Production; Optimization; Planning; Feed; Linear Programming. (search for similar items in EconPapers)
JEL-codes: C61 E23 (search for similar items in EconPapers)
Date: 2019-08
New Economics Papers: this item is included in nep-agr and nep-mac
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in International Journal of Applied Operational Research 3.9(2019): pp. 11-19

Downloads: (external link)
https://mpra.ub.uni-muenchen.de/98226/8/MPRA_paper_98226.pdf original version (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:pra:mprapa:98226

Access Statistics for this paper

More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().