Evolutionary computation is regarded as significant research area in computer science and has gained popularity in recent years because of its significant advantages as compared to deterministic methods. Evolutionary computation methods are highly preferred to solve multi-objective optimization problems where objective functions with conflicts are involved. It is regarded as a study of computational systems that makes use of ideas and is inspired from natural evolution and adaptation. Evolutionary computation techniques abstract evolutionary principles into algorithms to determine optimal solutions to various real-world problems. Evolutionary algorithms are concerned with investigating computational systems that resemble simplified versions of the processes and mechanisms of evolution, toward achieving the effects of these processes and mechanisms, namely the development of adaptive systems. The aim of this chapter is to introduce the area of Evolutionary Computation – Theory and Algorithms. The chapter provides an overview of the history and gives details regarding evolutionary algorithms – their working and components – and also highlights various computational models as well as approaches and applications in a detailed manner.