Course ID: D3
Unit: DATA SCIENCE AND ENGINEERING – Unit D: Data Analysis and Processing
Weekly Hours: 4
ECTS Credits: 7
Description:• Introduction to Optimization • Optimality conditions • One-dimensional optimization • Derivative-free methods: Steepest Descent, Nelder-Mead, Hook-Jeeves, Pattern Search. • Gradient-based methods: Newton, Quasi-Newton, Conjugate Gradients. • Line Search and Trust Region techniques. • Stochastic and evolutionary algorithms: Multistart, Simulated Annealing, Genetic Algorithms, Particle Swarm Optimization. • Solution techniques for constrained problems. • Techniques for the detection of multiple minimizers. Parallel coordinates.