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Published in

International Journal of ADVANCED AND APPLIED SCIENCES, 8(9), p. 65-71, 2022

DOI: 10.21833/ijaas.2022.08.008

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Optimal profitable applications for web development companies using a linear programming approach

Journal article published in 2022 by Khalid K. A. Abdullah, Saim Rasheed ORCID
This paper was not found in any repository; the policy of its publisher is unknown or unclear.
This paper was not found in any repository; the policy of its publisher is unknown or unclear.

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Abstract

The consumed resources in web development companies are different and greatly affect a company’s profit or loss extent. We will utilize linear programming to measure that and maximize the company’s profit. Furthermore, we will apply the simplex method algorithm within certain constraints placed on different components of the company's different products. This problem can be solved with a trial and error approach but this requires great effort and time, which is a challenging thing to do on each product. We can employ different computer tools that calculate and solve these problems. Microsoft Excel is one of these tools that solve linear programming equations and provides accurate outputs; there are plugins such as (Solver) that work in integration with Excel. This paper’s main goal and purpose are to calculate and acquire the ideal products that maximize the company's profit under certain constraints. The best distribution and optimal use of resources to increase profit while maintaining quality and quantification of each project type with imposed restrictions and steps that the company must take to stop and reduce excess and unused resources. The simplex method algorithm is used because it is faster than other algorithms in solving linear programming problems, and it has high efficiency in reducing the needed resources for computer processing. On the other hand, the limitations of this algorithm manifested in its dependence on variables will increase the complexity of the problem, and this cannot be implemented accurately in all cases of linear programming problems.