Production scheduling is one of the hardest optimization problems in manufacturing, balancing machine capacity, material availability, and delivery deadlines. This case study shows how DolphinDB, a high-performance time-series database, was used to build a complete intelligent scheduling system. The article walks through the entire journey: translating business rules into formal constraints, designing the optimization model, and deploying it as a production-ready service. Key highlights include how DolphinDB's vectorized computing and built-in analytics accelerate constraint solving, and how the system integrates with existing ERP and MES data. For engineers and architects in manufacturing, this is a rare, concrete example of applying modern data infrastructure to operational optimization. The approach is not limited to scheduling—the same pattern can be applied to inventory planning, logistics routing, and resource allocation.
A deep dive into building a production scheduling optimization system with DolphinDB, covering constraint modeling, algorithm design, and real-world deployment.