Evolutionary Algorithms for Optimization and Swarm Intelligence-Based Optimization
Rajeshwari Sissodia, ManMohan Singh Rauthan, Varun Barthwal, Vinay Kumar Dwivedi · Advances in systems analysis, software engineering, and high performance computing book series · 2025
Evolutionary Algorithms (EAs) and Swarm Intelligence (SI)-based Optimization are powerful, nature-inspired methodologies used to solve complex optimization problems. EAs, including Genetic Algorithms and Evolution Strategies, simulate natural selection processes to iteratively improve solutions through selection, mutation, and crossover. On the other hand, SI-based techniques, such as Particle Swarm Optimization and Ant Colony Optimization, draw from the collective behaviors of social organisms to effectively explore solution spaces. This chapter provides an overview of these approaches, examining their underlying principles, key algorithms, and applications in various fields. It also compares their strengths, discusses hybrid strategies that combine EAs and SI techniques, and explores future trends in optimization research.