The first part of this book focuses on methods that address scientific questions like how to balance convergence and diversity in the objective space, how to balance exploration and exploitation in the decision space, and how to effectively reduce dimensions. It presents a systematic study in this regard. Additionally, concerning the typical NP-hard engineering optimization problem of Flexible Job-shop Scheduling Problem (FJSP), this book explores solutions based on evolutionary optimization. It delves into the hybrid harmony search (HHS) method for single-objective optimization problems, the integrated search method combining hybrid harmony search and large neighborhood search (HHS/LNS) for high-dimensional single-objective optimization, and the memetic evolution method based on decomposing target importance for multi-objective optimization. Remarkable results have been achieved on multiple benchmark datasets.