Enhancing Decision-Making Processes in Operation Research through Artificial Intelligence Techniques in China

نوع المستند : الأبحاث العلمية الأصيلة

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تعليمي بحثي

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Enhancing Decision-Making Processes in Operation Research through Artificial Intelligence Techniques in China

Dr Dalia Younis



Arab Academy for Science and Technology and Maritime Transport



This research explores the integration of artificial intelligence (AI) techniques into operational research (OR) to enhance decision-making processes in various sectors across China. The study highlights how AI algorithms—such as machine learning, neural networks, and expert systems—are revolutionizing traditional OR models by increasing accuracy, efficiency, and adaptability. Through case studies and empirical data from Chinese industries, the paper investigates the practical applications of AI-enhanced OR in logistics, manufacturing, healthcare, and public services. The research also addresses challenges such as data availability, model interpretability, and the ethical implications of AI-driven decisions. Ultimately, the findings suggest that AI can significantly improve decision-making outcomes by providing real-time insights and predictive analytics, thereby supporting strategic planning and operational efficiency in China's rapidly evolving economy.

Keywords: Artificial Intelligence, Operations Research, Decision-Making, China, Cost Reduction, Resource Optimization, Sustainability, Ethics

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