Abstract
Production scheduling is a critical component of manufacturing and service industries, directly impacting operational efficiency, resource utilization, and delivery performance. The advent of Artificial Intelligence (AI) has revolutionized traditional scheduling approaches by enabling dynamic, adaptive, and data-driven decision-making. This article explores the integration of AI techniques such as machine learning, reinforcement learning, and heuristic optimization in production scheduling. It reviews key AI methodologies, their applications in complex scheduling environments, and the benefits of AI-driven scheduling systems including improved throughput, reduced lead times, and enhanced flexibility. Challenges and future research directions for AI-based production scheduling are also discussed.
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