This course introduces the principal algorithms for optimization. Optimization theory and methods that learned through the course help students understand optimization problems and develop algorithms and tools necessary for a wide range of design problems. We will learn
- Unconstrained/constrained optimization
- Least squares analysis
- Random search algorithm
- Linear programming
- Nonlinear constrained optimization
- Convex optimization
The newton’s method is a widely used algorithm to find the optimum point through quadratic approximation. At the expense of the complexity of obtaining the second moment, It works much faster in most applications than the linear approximation method.