Numerical optimization is a field that sits at the intersection of mathematics and computer science. It involves developing algorithms and computational techniques to find the best solution to a given problem from a set of possible solutions. This is particularly useful in various practical applications across science, engineering, and economics, where finding the optimal solution can be complex or even impossible using traditional analytical methods. In cases where traditional optimization approaches struggle to find solutions, natural computing offers a promising alternative. Natural computing is a field that draws inspiration from natural systems and processes to develop computational algorithms. These algorithms can be particularly effective for solving hard optimization problems, often yielding nearoptimal solutions. "Numerical Optimization" serves as a comprehensive reference for researchers, practitioners, and students seeking a deep understanding of optimization methods and their applications. The primary objective of this book is to present a unified and accessible treatment of the fundamental concepts, algorithms, and theoretical foundations underpinning numerical optimization.