Search Results for linear-programming

Abstract

The establishment is considered the center of strength for the economy of any country by meeting the needs of the community in terms of goods and services. Determining the optimal combination of production in light of the constraints of energy and demand is one of the most important pillars of the success of the establishment or factory in the market, noting that it depends on searching for the desired quantities of products based on the limited and scarcity of resources and energies. productivity required for production.

The linear programming model is among the most important quantitative methods used in building the mathematical model that enables decision-makers and those in charge of implementing them to reach the required goals in light of the available capabilities, as it is used to determine the optimal distribution of scarce resources, which usually include raw materials involved in the production process and machinery. equipment, allotted time and capital, and it is applied to many work problems and in various fields such as finance, production, marketing, distribution, etc.

Abstract

The goal of the paper is to reach the optimal decision by building the Fuzzy Linear Programming Model (FLPM) with fuzzy parameters represented by demand and production quantities. The study problem lies in the range that the model contributes to removing the uncertainty in determining the optimal amount of production, and to reach this value, available programs (MatlabV.10, Win Q.S.B V.2) were used to obtain the results of the optimal solution. The hypothesis of this study is that the Fuzzy Inference System (FIS) contributes to the uncertainty of the amount of production and demand. The research was based on an applied study of real data taken from the Iraqi General Cement Company, which is one of the most active companies in the Iraqi industry environment. Four factories (Kufa, Najaf, Babylon, Badoush al tawseea) were selected with their sample products for the company. The study used the model's order quantities, production requirements, and production quantity with Triangular Fuzzy Numbers (TFN). One of the most important conclusions reached by the researcher is that the data adopted from the four factors and the results of the analysis are that the output in these coefficients is fuzzy and unstable, and that the application of fuzzy logic is an effective way to get rid of the uncertainty.