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Profit Maximization in a Product Mix Bakery Using Linear Programming Technique
Journal of Investment and Management
Volume 9, Issue 1, March 2020, Pages: 27-30
Received: May 10, 2019; Accepted: Jan. 13, 2020; Published: Mar. 6, 2020
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Kayode Olakunle Oluwaseyi, Department of Business Administration, University of Benin, Benin City, Nigeria
Atsegameh Elizabeth, Department of Business Administration, University of Benin, Benin City, Nigeria
Omole Ezekiel Olaoluwa, Department of Mathematics & Statistics, Joseph Ayo Babalola University, Ikeji-Arakeji, Osun State, Nigeria
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Linear Programming is one of the optimization techniques in finding solutions to managerial decisions making. Linear Programming is a widely used mathematical modelling technique designed to help managers in planning and decisions making relative to resource allocation. This study applied linear programming technique to decision making problem in university of Benin Bakery, Benin city, Edo state, Nigeria, and intended to determine the quantity of Bread that the firm should produce in a day to maximize profit, subject to constraints in the production process. Data on quantity of major raw material used in production of large, medium and small size bread per day were collected from the extract of the financial record of the bakery. The problem was formulated in mathematical term and solved using computer software known as Linear Programming Solver (LIPS). The solution obtained from a single iteration showed that 667 units of extra- large bread should be produced daily for the firm to achieve a maximum daily profit of #100,000. It is therefore recommended that the firm should concentrate more on production of extra- large bread to obtain maximum profit of #100,000 per day.
Linear Programming, Optimization Problem, Simplex Method, Linear Programming Solver
To cite this article
Kayode Olakunle Oluwaseyi, Atsegameh Elizabeth, Omole Ezekiel Olaoluwa, Profit Maximization in a Product Mix Bakery Using Linear Programming Technique, Journal of Investment and Management. Vol. 9, No. 1, 2020, pp. 27-30. doi: 10.11648/j.jim.20200901.14
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This article is an open access article distributed under the Creative Commons Attribution License ( which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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