Profit Optimization of an Apparel Industry in Bangladesh by Linear Programming Model
American Journal of Applied Mathematics
Volume 8, Issue 4, August 2020, Pages: 182-189
Received: Mar. 11, 2020;
Accepted: Mar. 27, 2020;
Published: Jul. 17, 2020
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F. M. Shakirullah, Department of Mathematics, Dhaka University of Engineering and Technology, Gazipur, Bangladesh
Main Uddin Ahammad, Department of Mathematics, Dhaka University of Engineering and Technology, Gazipur, Bangladesh
Mohammed Forhad Uddin, Department of Mathematics, Bangladesh University of Engineering and Technology, Dhaka, Bangladesh
Efficient use of resources in production stages is very much important for every industry. For sustainable development of industry, efficacious management decision making techniques may be employed to analyze and utilize resources. Linear programming, as a quantitative decision-making tool, can be engaged by the managements for enhancing resource utilization along with increasing profit and decreasing cost. Proper allocation and usage of resources like available processing time at different stages, labors, materials such as fabrics and sewing threads is the tacit factor for profitability of an apparel manufacturing firm. Apparel processes such as cutting, sewing, washing, dying, trimming and finishing are needed to be optimized for lead time management. This study formulated a linear programming model to maximize profit and minimize cost of apparel industries. The model also optimizes the utilization of resources. This paper considers a knit garment manufacturing unit of Bangladesh which is situated in Gazipur district. Data containing monthly resources utilization amount, product volume, profit per unit on different types of products have been collected from the case industry. The data collected was used as the parameters of the proposed linear programming to validate the model. The model was implemented and solved by the Microsoft Excel Solver as well by AMPL. This research revealed that the profit of the case company can be increased by 22% when there is sufficient demand and that can be 12.33% when clients’ requests are to be met. On the other hand, cost may be decreased by 37% by using the LPP model.
F. M. Shakirullah,
Main Uddin Ahammad,
Mohammed Forhad Uddin,
Profit Optimization of an Apparel Industry in Bangladesh by Linear Programming Model, American Journal of Applied Mathematics.
Vol. 8, No. 4,
2020, pp. 182-189.
Uddin, M. F. and Sano, K. (2012). Coordination and Optimization: The Integrated Supply Chain Analysis with Non-Linear Price-Sensitive Demand, An International Journal of Optimization and Control: Theories & Applications, 2, 1, 83-94.
Jokar, M. R. and Sajadieh, M. S. (2009). Optimization a Joint Economic Lot Sizing Problem with Price-sensitive Demand, Transaction E: Industrial Engineering, 16, 2, 159-164.
Qin, Y., Tang, H. and Guo, C. (2007). Channel Coordination and Volume Discounts with Price-sensitive Demand. Int. J. Production Economics, 105, 43-53.
Uddin, M. F. and Sano, K. (2010). Mixed Integer Linear Fractional Programming for Integrated Supply Chain Network Design and Optimization, International Journal of Business and Economics, 2, 1, 57-70.
Uddin, M. F. and Sano, K. (2011). Coordination, Supply Chain Optimization and Facility Location Selection Problem, Journal of Society for Transportation and Traffic Studies, 2, 3, 18-32.
Islam, M. K., Uddin, M. F. and Alam, M. M. (2014). Supply Chain Optimization by Mixed Integer Program for Manufacturer and Retailer System of Poultry Firm in Bangladesh, Journal of Bangladesh Mathematical Society, 34, 75-87.
Islam, M. K., Uddin, M. F. and Alam, M. M. (2015). Comparison and Supply Chain Optimization of Poultry Firm Using Mixed Integer and Linear Fractional Program. IOSR Journal of Mathematics, 11, 1, 40-54.
Momaya, K. (2008). Evaluating Country Competitiveness in Emerging Industries: Learning from a Case of Nanotechnology, Journal of International Business and Economy, 9, 1, 37-58.
Nandita, B. and Hasan, M. B. (2017). A Sophisticated Forecasting Method for a Garments Company in Bangladesh, International Journal of Pure and Applied Mathematics, 117, 14, 145-156.
Kumar, V. (2010). JIT Based Quality Management: Concept and Implications in Indian Context. International Journal of Engineering Science and Technology, 2, 1, 40-50.
Ezema, B. I. and Amakom, U. (2012). Optimizing Profit with the Linear Programming Model: A Focus on Golden Plastic Industry Limited, Enugu, Nigeria. Interdisciplinary Journal of Research in Busness, 2, 2, 37-49.
Yalçinsoy, A., Zincirkiran, M. and Tiftik, H. (2014). Approach of Capacity Planning Through Linear Programming Technique: A Practice in Textile Enterprise. International Journal of Innovative Research in Management, 3, 3, 16-29.
Campo, E. A., Cano, J. A., Andres, R. and Montoya, G (2018). Linear Programming for Aggregate Production Planning in a Textile Company. Fabric and Textiles in Eastern Europe, 26, 5 (131), 13-19.
Woubante, G. W. (2017). The Optimization Problem of Product Mix and Linear Programming Application: Case Study in the Apparel Industry. Open Science Journal, 2, 2, 1-11.
Tesfaye, G., Berhane, T., Zenebe, B. and Asmelash, S. (2016). A Linear Programming Method to Enhance Resource Utilization Case of Ethiopian Apparel Sector. International Journal for Quality Research, 10, 2, 421-432.