Nature-Inspired Optimization Algorithms (original) (raw)

Nature-inspired optimization algorithms, including swarm intelligence-based methods like particle swarm optimization and firefly algorithms, have gained popularity due to their efficacy. This book reviews significant advancements in various algorithms, such as genetic algorithms, simulated annealing, and hybrid strategies. It emphasizes foundational algorithm concepts, key implementation steps, and highlights existing gaps in theory versus practical application, ultimately suggesting directions for future research in algorithm convergence, parameter tuning, and optimization challenges.