Multivariable control systems design and optimization addresses the task of regulating multiple interdependent process variables within a single framework. Unlike single‐loop controllers, ...

1 School of Aeronautics and Astronautics, Sun Yat-sen University, Guangzhou, China. 2 School of Science and Technology, Hunan University of Technology, Zhuzhou, China. To address the multicoupling ...

Optimization is a crucial tool throughout science and technology. Large datasets and high dimensional problems create unique challenges for standard optimization techniques such as Newton’s method, ...

The Simulated Bifurcation (SB) algorithm is a fast and highly parallelizable state-of-the-art algorithm for quadratic combinatorial optimization inspired by quantum physics and spins dynamics. It ...

The Poisson lognormal model and variants 1 can be used for a variety of multivariate problems when count data are at play. This package implements efficient variational algorithms to fit such models, ...

Abstract: The binary polarization state analyzer (PSA) made of magnetooptic crystal (MO) rotators is a promising technology for achieving low-cost and high-efficiency state of polarization (SOP) ...

This work presents a generalized approach for analytical method optimization that branches the gap between techniques historically employed and accurate modern optimization techniques suitable for ...

Nature-inspired metaheuristic algorithms are important components of artificial intelligence, and are increasingly used across disciplines to tackle various types of challenging optimization problems.

Abstract: We extend the relation between univariate polynomial optimization in one complex variable and the polynomial eigenvalue problem to the multivariate case. The first-order necessary conditions ...

Despite the success of multiscale modeling in science and engineering, embedding molecular-level information into nonlinear reactor design and control optimization problems remains challenging. In ...