Our approach introduces the first general Learning-to-Optimize (L2O) framework designed for Mixed-Integer Nonlinear Programming (MINLP). As illustrated above, the approach consists of two core ...

Abstract: Nonlinear model predictive control (NMPC) has proven its ability to control constrained nonlinear processes. Although NMPC can achieve exemplary tracking performance, the related computation ...

Abstract: Nonlinear Model Predictive Control (NMPC) is an effective method for motion planning of automated vehicles, but the high computational load of numerical optimization limits its practical ...

We propose a new trust region algorithm for nonlinear constrained optimization problems. In each iteration of our algorithm, the trial step is computed by minimizing a quadratic approximation to the ...

Adam Hayes, Ph.D., CFA, is a financial writer with 15+ years Wall Street experience as a derivatives trader. Besides his extensive derivative trading expertise, Adam is an expert in economics and ...