Optimizing resources is a paramount issue in engineering applications. However, traditional optimization tools often struggle to address real-world complex problems effectively. The emergence of advanced nature-inspired optimization algorithms has provided solutions to these challenges. These algorithms, drawing inspiration from natural processes such as evolution, swarm intelligence, and natural selection, have revolutionized the field by offering robust, flexible, and efficient optimization techniques. In this chapter, we present a brief discussion on the contribution of nature-inspired optimization algorithms in the history of engineering optimization. We explore key milestones and developments, showcasing how these algorithms have evolved to tackle increasingly complex problems. Additionally, we highlight the diverse range of applications where nature-inspired algorithms have proven effective, from structural optimization in civil engineering to scheduling and routing, software testing, image processing, data mining, energy management, heat transfer problems, and mechanical design. This chapter introduces the main topics discussed in this book, providing a roadmap for exploring the various applications and innovations driven by nature-inspired optimization in engineering. Through this overview, we aim to equip readers with the knowledge and insights needed to harness the power of these algorithms in their own engineering endeavors, ultimately contributing to more efficient, innovative, and practical solutions in their respective fields.