An AI Optimization Pipeline is a structured workflow that continuously processes data, evaluates possible actions, and selects or refines solutions according to defined objectives and constraints. Unlike a conventional data pipeline that primarily moves or transforms information, an optimization pipeline uses models and optimization algorithms to determine the most effective outcome.
A typical pipeline may combine data preparation, prediction, constraint handling, optimization, evaluation, and deployment. It can dynamically adjust decisions as new information arrives, making it useful for applications such as production scheduling, logistics, energy distribution, pricing, inventory planning, and cloud resource allocation.
