The Role of Linear Programming in Investment Decision Making (A case study at Sama Al- Reef Company)

Abstract

The research aims to make a long-term investment decision that enables the economic unit to continue and achieve long-term profits using the method of linear programming on the proposed investment projects implemented by "Sama Al-Rif Agricultural and Animal Production Company Limited" as an applied case due to the diversity of its investment projects and the multiplicity of alternatives available to it. The research problem was the poor accuracy of investment decisions when relying on traditional methods of decision-making, which often depend on personal judgment and accumulated experience without the use of quantitative and systematic analysis. Perhaps linear programming is the best tool in solving this problem as a mathematical method used for planning and optimal decision-making purposes in light of limited resources and can be described as an important method to support the decision maker in making the best decision based on scientific methods. The Simplex Method was used among the different methods and methods of the linear programming model because it is one of the appropriate methods to reach the desired goal in light of the multiplicity of investment projects. The researcher used the quantitative analysis method using the (winQsb) program to build the mathematical model and apply it to the data of (4) four proposed investment projects. The research came up with a set of conclusions, the most important of which is the selection of only three (3) investment projects, while high-cost and low-return projects were excluded, reflecting the efficiency of performance in supporting the decision. The research has proven that linear programming is an effective tool for rationalizing investment decisions, and enhances the efficiency of resource allocation by focusing on the most profitable projects. The research also recommended the need to generalize the use of the linear programming model in the public and private sectors and train the concerned cadres in the use of modern analytical programs.