Meta-Heuristic Paradigms and Swarm-Based Models for Large-Scale Optimization

Swarm Intelligence and other metaheuristics have recently gained attention as optimization methods in large-scale data analytics, particularly in control engineering. With the increasing use of big data, IoT devices, and real-time processing, traditional techniques are facing challenges in dealing with high-dimensional and nonlinear problems. Swarm intelligence methods are based on the collective behavior of natural systems, providing robust and scalable solutions for optimizing control parameters, system identification, and fault detection in large environments. The combined use of swarm intelligence and metaheuristics will improve optimization for control engineering applications, focusing on large-scale analytics as discussed in this chapter. Case studies presented in this chapter demonstrate the effectiveness of these methods in optimizing complex control systems where traditional methods struggle due to size or complexity.