Dec 23, 2024 · In this study, emphasis is given towards examining the abilities of three heuristic optimization control methods – PSO, GA, and a hybrid genetic particle swarm optimization …

Dec 20, 2023 · Both the genetic algorithm and the particle swarm optimization algorithm aim to solve optimization problems by finding the best possible solution. They both work by exploring …

This paper introduces a novel approach to accelerate genetic optimization in Nonlinear Model Predictive Control (NMPC) by dynamically learning the optimal search space size.

Jan 1, 2024 · Metaheuristic optimization algorithms offer an alternative to traditional optimization methods, as they can quickly reach near-optimal solutions and avoid local minima, making …

1 day ago · Currently, MOO algorithms, such as the Non-dominated Sorting Genetic Algorithm (NSGA) 21,22, Multi-Objective Particle Swarm Optimization (MOPSO) 23, and Multi-Objective …

Mar 26, 2025 · In this study, we propose a hybrid approach that integrates genetic algorithm (GA) optimization and particle swarm optimization (PSO) with machine learning techniques to …

May 6, 2025 · Many new algorithms have been proposed and optimized to enhance the performance of MOPs 8, such as Particle Swarm Optimization (PSO) 9, Genetic Algorithm …

1 day ago · Furthermore, by combining these control problems with two experimental settings that differ in scale and complexity, we conduct a comprehensive evaluation of several …

Aug 21, 2024 · Our contributions include a novel GA-based MPC strategy, the ability to control with the system’s nonlinear model, and outperforming existing strategies in CSTR control.

Intro: PSO vs. GAs Similarities: – Iteration based – Start with pool of initial values – Both heuristic algorithms Differences: – Continuous (PSO) vs. Discrete (GA) Can we prove which is more …