Graduate Program in Biotechnology, Federal University of Pará, Belém 66075-110, Brazil Graduate Program in Process Engineering, Federal University of Pará, Belém 66075-110, Brazil Faculty of Chemical ...

Abstract: In recent years, numerous recurrent neural network (RNN) models have been reported for solving time-dependent nonlinear optimization problems. However, few existing RNN models simultaneously ...

We study some nonlinear optimal control problems under state constraint. We construct extremal flows by differential-algebraic equations to solve an optimal control problem subject to mixed ...

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 ...

Abstract: Recently, recurrent neural network (RNN) models have been extensively investigated for addressing time-dependent nonlinear optimization problems. However, few existing RNN models take ...

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

Zeroing neural network (ZNN) is viewed as an effective solution to time-varying nonlinear equation (TVNE). In this paper, a further study is shown by proposing a novel combined discrete-time ZNN ...

This work extends our prior work on the distributed nonlinear model predictive control (NMPC) for navigating a robot fleet following a certain flocking behavior in unknown obstructed environments with ...

This workshop on Engineering Design Optimization using MATLAB® and Python™ addresses the shape optimization of mechanical components for strength. Python ...

Researchers at Cornell University in the U.S. have developed a novel optimization model for agrivoltaic site design and benefits, which was demonstrated using irrigation-optimization relative to ...