There is no wealth like Knowledge
                            No Poverty like Ignorance
ARPN Journals

ARPN Journal of Engineering and Applied Sciences >> Call for Papers

ARPN Journal of Engineering and Applied Sciences

Simplex method for profit maximization in Chinese breakfast food stall

Full Text Pdf Pdf
Author Lim Eng Aik, Tan Wee Choon, Tan Wei Hong and Cheng Ee Meng
e-ISSN 1819-6608
On Pages 151-155
Volume No. 18
Issue No. 03
Issue Date March 18, 2023
Keywords linear programming, optimization problem, simplex method, operational research, food stall.


Linear programming is an operational research technique widely used to identify action solutions for managers. The linear programming model explores the efficient use of available raw materials to produce different marketable products. Linear programming will encourage companies to increase production by taking full advantage of this opportunity. However, the trial-and-error approach is most often used by many organizations. As a result, firms find it challenging to allocate scarce resources in a profit-maximizing manner. This study focuses on implementing optimization principles to optimize manufacturing revenues through linear programming to measure production costs and determine their optimal benefits. The study uses data from Chinese food stall reports for five breakfast types: nasi lemak, fritters, curry puff, ear-eye cake, and popiah. The attribute has been identified as a linear programming problem, built mathematically and solved using Excel software. The results show that the food stall should concentrate more on producing curry puff and popiah. In comparison, other products should be produced less because their value becomes zero to reach the maximum monthly profit of RM28, 236. The analysis found that curry puff and popiah objectively contribute to the revenue. Therefore, more curry puff and popiah must be produced and sold to maximize profit.


GoogleCustom Search

Seperator Publishing Policy Review Process Code of Ethics

© 2023 ARPN Publishers