Ammar Kuti Nasser
AI is used in operations research models to strengthen the decision support mechanism as well as optimization and prediction results.
To give a concrete example, Considering the operational system of an e-commerce company, we can evaluate it as developing a dynamic vehicle route model using artificial intelligence for optimization. AI-supported genetic algorithms determine the best routes to shorten delivery times and reduce fuel costs. This reduces operational costs and increases customer satisfaction.
The company can also predict customers' future demand using machine learning models for forecasting. Past sales data, seasonality, and consumer behavior are analyzed to predict which products will sell more in which period. This way, stock management is optimized, and excess inventory costs can be reduced.
Finally, decision support systems can be powered by AI to suggest the best strategy for managers. Prescriptive analytics methods analyze sales trends, supply chain status, and customer feedback and provide recommendations on which products should be sent to which markets as a priority. This helps the company make more informed and data-driven decisions.
It is used in a number of ways, from route planning to preventive maintenance.
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