This book comprises peer-reviewed papers presented at the 5th International Conference on Advanced Engineering Optimization Through Intelligent Techniques (AEOTIT) 2024. It combines contributions from academics and industry professionals, covering advanced optimization techniques across major engineering disciplines. The book discusses various optimization techniques and algorithms such as genetic algorithms, particle swarm optimization, differential evolution, whale optimization algorithm, artificial bee colony algorithm, arithmetic optimization algorithm, beat-worst-random and best-mean-random algorithms, teaching–learning-based optimization algorithm, gray wolf optimization, Jaya algorithm, Rao algorithms, and many other latest meta-heuristic techniques. It also explores several machine learning algorithms and their applications. Additionally, the book explores various multi-attribute decision-making methods such as AHP, TOPSIS, PROMETHEE, dominance-relations based method, Taguchi method, fuzzy logic, and their applications. This book serves as a valuable reference for students, researchers, and practitioners, helping them solve a wide range of optimization problems.
