Modern semiconductor chip design faces growing complexity due to numerous timing scenarios driven by varying operating ...

Qlik® announced the general availability of its Multivariate Time Series (MVTS) capability in Qlik Predict™, bringing ...

The article debunks the common belief that trial-and-error improvements equate to true optimization. It provides a deep dive into how RTO works—from mathematical ...

Introduction: We present Quantum Adaptive Search (QAGS), a hybrid quantum-classical algorithm for global optimization of multivariate functions. The method employs an adaptive mechanism that ...

Implementation of numerical optimization algorithms in MATLAB, including derivative-free and gradient-based methods for unconstrained problems, and projection techniques for constrained optimization.

Artificial intelligence (AI) is playing a huge role in heat rate optimization. In some cases, AI-driven models have analyzed operational data to recommend control settings that reduce heat rates by ...

Abstract: A simplified MIMO constrained controller is proposed. Based on the steady-state prediction of system outputs, the controller combines steady-state optimization and dynamic control ...

One of the major goals that field planning engineers and decision makers have to achieve in terms of reservoir management and hydrocarbon recovery optimization is the maximization of return on ...

We tackle the problem of high-dimensional nonparametric density estimation by taking the class of log-concave densities on ℝp and incorporating within it symmetry assumptions, which facilitate ...