Numerical Techniques

Optimization techniques are essential for identifying the best solution from a set of options across various fields including operations research, economics, and engineering. Key methodologies discussed include Linear Programming, Nonlinear Programming, and Gradient-based Methods, each serving unique types of problems and constraints. The chapter provides insights into tools and methods such as the Simplex method, Gradient Descent, and the use of the Duality principle in optimization.