Online Optimization refers to the process of continuously optimizing the performance of a system in real-time based on feedback from the environment. It involves making decisions that maximize a specific objective or utility function, taking into account constraints and uncertainties. Online optimization is commonly used in e-commerce, finance, and advertising to make real-time decisions about pricing, bidding, and targeting, among others.

The goal is to maximize revenue or profit while minimizing costs and risks. The optimization process involves collecting data, analyzing it, and using it to update the model or algorithm in real-time, enabling the system to adapt to changing conditions and improve its performance continuously. Online optimization requires efficient algorithms and models that can make decisions quickly and accurately, as well as a robust infrastructure that can handle large volumes of data and perform real-time computations. Overall, online optimization is a critical component of many modern systems, enabling real-time decision making and improving their overall efficiency and effectiveness.