This book comprises peer-reviewed papers presented at the 4th International Conference on Advanced Engineering Optimization Through Intelligent Techniques (AEOTIT) 2023. The book combines contributions from academics and industry professionals and covers advanced optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil,  electrical, chemical, computer, and electronics engineering. The book discusses different optimization techniques and algorithms such as genetic algorithm, non-dominated sorting genetic algorithm-II, and III,  particle swarm optimization, gravitational search algorithm, ant lion optimization, dragonfly algorithm, teaching–learning-based optimization algorithm, grey wolf optimization, Jaya algorithm, Rao algorithms, many other latest meta-heuristic techniques, machine learning algorithms, and their applications. Various multi-attribute decision-making methods such as AHP, TOPSIS,  PROMETHEE, desirability function,  SWARA, R-method, BHARAT method, Taguchi method, fuzzy logic, and their applications are also discussed. This book serves as a valuable reference for students, researchers, and practitioners and helps them in solving a wide range of optimization problems.

This book comprises peer-reviewed papers presented at the 4th International Conference on Advanced Engineering Optimization Through Intelligent Techniques (AEOTIT) 2023. The book combines contributions from academics and industry professionals and covers advanced optimization techniques across all major engineering disciplines like mechanical, manufacturing, civil,  electrical, chemical, computer, and electronics engineering. The book discusses different optimization techniques and algorithms such as genetic algorithm, non-dominated sorting genetic algorithm-II, and III,  particle swarm optimization, gravitational search algorithm, ant lion optimization, dragonfly algorithm, teaching–learning-based optimization algorithm, grey wolf optimization, Jaya algorithm, Rao algorithms, many other latest meta-heuristic techniques, machine learning algorithms, and their applications. Various multi-attribute decision-making methods such as AHP, TOPSIS,  PROMETHEE, desirability function,  SWARA, R-method, BHARAT method, Taguchi method, fuzzy logic, and their applications are also discussed. This book serves as a valuable reference for students, researchers, and practitioners and helps them in solving a wide range of optimization problems.