Abstract: The successive convex approximation (SCA) methods stand out as the viable option for nonlinear optimization-based control, as it effectively addresses the challenges posed by nonlinear ...

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: Multi-objective optimization remains a significant and realistic problem in engineering. A trade-off among conflicting objectives subject to equality and inequality constraints is known as ...

Machine learning models are increasingly applied across scientific disciplines, yet their effectiveness often hinges on heuristic decisions such as data transformations, training strategies, and model ...

Aim to minimize the combined fixed and transportation costs by deciding which of five plants to keep open or what have to close.

In this blog, we will discuss how Keysight RF Circuit Simulation Professional revamps RF circuit simulation and optimization. Discover how to achieve efficient, accurate designs for even the most ...

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...

This repository contains the implementation of a parallel solver for Fisher’s equation using MPI and High-Performance Computing (HPC) with Python. The project builds on previous work with OpenMP and ...