Production Planning

Production planning aims to optimize manufacturing processes by efficiently scheduling resources and tasks to meet production goals, such as minimizing production time or maximizing throughput. Current research emphasizes the use of advanced algorithms, including reinforcement learning, evolutionary algorithms, and machine learning techniques like quantile regression forests, to address the complexities of real-world scenarios, such as fluctuating demand, supply chain disruptions, and machine setup times. These efforts are driven by the need for improved efficiency, flexibility (especially in reconfigurable manufacturing systems), and the ability to handle mass customization and the uncertainties inherent in modern manufacturing. The resulting improvements in production planning have significant implications for cost reduction, increased productivity, and enhanced responsiveness to market demands.