8 Unleashing the Power of Evolutionary Algorithms: Advanced Optimization Techniques in Artificial Intelligence
Yogesh Kumar Sharma, Uppuluri Lakshmi Soundharya, Ravi Rastogi, Anand Raman · 2025
The exploration of practical optimization approaches is constant within artificial intelligence (AI). Among several methods, evolutionary algorithms (EAs) stand out as powerful tools, deriving influence from the selection processes by nature and the evolution of genes. This chapter explores the complexities of EAs, explaining how they work, their many uses in AI, the obstacles they present, and the directions of future improvements. This study thoroughly examines modern optimization algorithms, discussing difficulties and suggesting possible directions for further investigation. The examination covers various optimization methods in several fields, including mathematical programming, machine learning, and AI. The text examines the fundamental difficulties encountered by current algorithms, such as problems with scalability, speed of convergence, and capacity to adapt to different problem domains. In addition, the study thoroughly analyzes the influence of optimization algorithms on practical applications, considering their efficacy and constraints. The study highlights developing trends, including hybrid techniques and metaheuristic methodologies, which show promise in addressing contemporary difficulties. This chapter offers a comprehensive overview of the most advanced optimization algorithms. It serves as a helpful reference for academics, practitioners, and decision-makers, helping them overcome current restrictions and explore new possibilities in the field of optimization research.