In this paper, a mathematical model was built for the supply chain to reduce production, inventory, and transportation in Baghdad Company for Soft Drink. The linear programming method was used to solve this mathematical model. We reduced the cost of production by reduced the daily work hours, the company do not need the overtime hours to work at the same levels of production, and the costs of storage in the company's warehouses and agents' stores have been reduced by making use of the stock correctly, which guarantees reducing costs and preserving products from damage. The units transferred from the company were equal to the units demanded by the agents. The company's mathematical model also achieved profits by (84,663,769) by reducing the total costs to (825,843,231), while the total cost in the company was (910,507,000)
Abstract
The multiple linear regression model of the important regression models used in the analysis for different fields of science Such as business, economics, medicine and social sciences high in data has undesirable effects on analysis results . The multicollinearity is a major problem in multiple linear regression. In its simplest state, it leads to the departure of the model parameter that is capable of its scientific properties, Also there is an important problem in regression analysis is the presence of high leverage points in the data have undesirable effects on the results of the analysis , In this research , we present some of
... Show MoreArabic text classification is a challenging task because of the complex morphology of the language, the existence of different writing forms and a multitude of dialects, which can result in sparser common text representations. While transformer models such as AraBERT have obtained superior results on many Arabic NLP tasks, their high computational requirements make them difficult to deploy in environments with limited hardware resources. In some cases this can also make the model less practical for researchers working with basic computer systems. This study focuses on a more practical issue: how much accuracy a simple classifier may lose when the amount of required computation is reduced. We use a combined TF-IDF representation based on bo
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