Profit Optimization Using Linear Programming Model: A Case Study of Ethiopian Chemical Company
American Journal of Biological and Environmental Statistics
Volume 1, Issue 2, September 2015, Pages: 51-57
Received: Oct. 12, 2015; Accepted: Apr. 15, 2016; Published: Jun. 16, 2016
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Authors
Vishwa Nath Maurya, Department of Applied Mathematics and Statistics, School of Science & Technology, The University of Fiji, Lautoka, Fiji
Ram Bilas Misra, Department of Mathematics & Computing Science, Divine Word University, Madang, Papua New Guinea
Peter K Anderson, Dept. of Information Systems, and Dept. of Mathematics & Computing Science, Divine Word University, Madang, Papua New Guinea
Kamlesh Kumar Shukla, Department of Management, Adama Science and Technology University, Adama, Ethiopia
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Abstract
This paper aims for profit optimization of an Ethiopian chemical company located in Adama (Ethiopia) using linear programming model. Particularly, our present study brings out clearly the necessity of using quantitative techniques for utilization in Ethiopian company; a factory situated within Adama about 90 kms. from Addis Ababa (Capital of Ethiopia). The first step comprises data generation. A questionnaire is prepared and circulated amongst company staff both executive and technical to determine the production, sales and profit during a few months of 2014. The profits varied considerably owing to subjective approach. It was established that the decisions are undertaken by experienced people without use of quantitative people and quantitative method. Whole approach applied here is seemingly subjective. A theoretical perspective undertaken for the present study is review of various different applications of linear programming. The characteristics of base assumptions of linear programming and its advantages and disadvantages towards establishing its need for optimization are briefly outlined in terms of its application to the factory. Survey data is analyzed to determine the style of decision making and the problem is defined. An objective function is created in terms of decision variables of production, sales and profit over a period of time using the quantitatively available data of these parameters. A linear programming model for company is developed for profit optimization. The model equations with adequate restraints taking into account manufacturing limitations are solved using MS-Excel solver. Finally, some conclusive observations have been drawn and recommendations have been suggested.
Keywords
Profit optimization, linear programming model, simplex method, manufacturing limitation, service industries
To cite this article
Vishwa Nath Maurya, Ram Bilas Misra, Peter K Anderson, Kamlesh Kumar Shukla, Profit Optimization Using Linear Programming Model: A Case Study of Ethiopian Chemical Company, American Journal of Biological and Environmental Statistics. Vol. 1, No. 2, 2015, pp. 51-57. doi: 10.11648/j.ajbes.20150102.12
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Copyright © 2015 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
References
[1]
Anderson, D.R.; Sweeney, D.J.; Williams, T.A.; Camm, J.D.; and Kipp, Martin:An Introduction to Management Science: Quantitative Approaches to Decision Making, Revised 13th ed., South-Western Cengage Learning, 2012.
[2]
Dantzig G.B., Programming of interdependent activities: II Mathematical Model, Econometrica, 17 (3), pp. 200–211, 1949. doi:10.2307/1905523.
[3]
Dantzig, G.B.: Compact basis triangularization for the simplex method, R.L. Graves and P. Wolfe (eds.), Recent Advances in Mathematical Programming, McGraw-Hill, New York, pp.125–132, 1963.
[4]
Drayer, W. and Seabury, S.: Linear programming - A case example, strategy & leadership, 3(5), pp.24-26, 1975.
[5]
Fagoyinbo, I.S.: Compendious text on quantitative techniques for professionals, Ilaro, Nigeria, Jombright Productions, 2008.
[6]
Frederick, H.S. and Lieberman, J.G.: Introduction to Operations Research, McGraw-Hill, Operations research - 1214 pages, 2001.
[7]
Kim, C.: Parametrizing an activity vector in linear programming, Operations Research, 19, pp.1632-1646, 1971.
[8]
Mehdipoor, E.; Sadr-ol-ashraafi, S.M. and Karbaasi, A.: A comparison of canonical linear programming techniques, Meaty Chicken’ Feed Farming with Linear Programming Models, Scientific-Research Magazine of Agriculture, 12(3), 2006.
[9]
Misra, R.B.: Numerical Analysis for solution of ordinary differential equations, Lambert Academic Publishers, Saarbrücken (Germany), 2010, ISBN 978-3-8433-8489-6.
[10]
Owen, P. and Mason, J.C.: The use of linear programming the design of antenna pattern with prescribed nulls and other constraints, compel: The International Journal for Computation and Mathematics in Electrical and Electronic Engineering, 3(4), pp.201-215, 1984.
[11]
Wijeratne, N. and Harris, F.C.: Capital budgeting using a linear programming model, International Journal of Operations & Production Management, 4(2), pp.49-64, 1984.
[12]
Williams, N.: Linear and non-linear programming in industry, Sir Isaac Pitman & Sons, Ltd., London. Garifinkel (1963). A solution of the Goddard problem, Journal of SIAM Control, 1(3), pp.349–368, 1963.
[13]
Wood, M.K. and Dantzig, G.B.: Programming of interdependent activities: I General Discussion. Econometrica, 17 (3/4): 193–91949. JSTOR1905522.
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