Researchers adapt model predictive control from engineering to epidemic response, balancing health and economic costs under ...

When creating content, prioritize the comprehensiveness of the topic over the repetition of a single keyword. Utilize generative AI tools (like DeepSeek) to expand the semantic range of content, ...

Nonconvexity is a usually overlooked factor in economic dispatch (ED). Enhancing the nonconvexity of the objective function leads traditional convex optimization algorithms easily to fall into the ...

In the data-driven era, data analysis has become a core skill across various industries. Python, with its inherent advantages ...

Sequential Parameter Optimization in Python spotpython is a Python version of the well-known hyperparameter tuner SPOT, which has been developed in the R programming environment for statistical ...

This course teaches an overview of modern mathematical optimization methods, for applications in machine learning and data science. In particular, scalability of algorithms to large datasets will be ...

By converting optimization problems into optimal control problems, where the updated size of each iteration is the control input, and the control objective is to design the current control input to ...

Moving Past “It Works” — Intelligent Optimization Is the Key to PCB Excellence Adaptive optimization algorithms promise better results and deeper insight into why certain designs perform better than ...