Checking date: 23/03/2024

Course: 2024/2025

Master in Computational and Applied Mathematics (Plan: 458 - Estudio: 372)

Coordinating teacher: MOSCOSO CASTRO, MIGUEL ANGEL

Department assigned to the subject: Mathematics Department

Type: Compulsory
ECTS Credits: 3.0 ECTS


Requirements (Subjects that are assumed to be known)
Students are expected to have a solid background in Linear Algebra and Calculus.
- To develop a theoretical basis and the skills for solving optimization problems arising in science and engineering. - To learn some of the more important optimization algorithms. Codes: CB6, CB7, CB8, CB9, CB10, CG2, CG4, CG5, CG6, CG7, CE1, CE2, CE3, CE4, CE8
Skills and learning outcomes
Description of contents: programme
1. Introduction to mathematical optimization. a. Unconstrained optimization. b. Equality constrained minimization. c. Inequality constrained minimization. 2. Convex optimization a. Convex sets and convex functions. b. Linear optimization problems. c. Quadratic optimization problems. 3. Duality a. The Lagrange dual function. b. The Lagrange dual problem. 4. Geometric problems 5. Other Applications
Learning activities and methodology
- Theoretical sessions illustrated with different applications and examples. Material for out-of-class work. - Problem sessions to discuss different problems in science and engineering. There will be proposed projects to be solved at home.
Assessment System
  • % end-of-term-examination 30
  • % of continuous assessment (assigments, laboratory, practicals...) 70

Calendar of Continuous assessment

Basic Bibliography
  • Ross Baldick. Applied optimization: formulation and algorithms for engineering systems. Cambridge University Press. 2009
  • S. Boyd and L. Vandenberghe. Convex Optimization. Cambridge University Press. 2004
Recursos electrónicosElectronic Resources *
Additional Bibliography
  • David G. Luenberger and Yinyu Ye. Linear and Nonlinear Programming. 3rd ed. Springer. 2008
  • Jorge Nocedal and Stephen J. Wright. Numerical Optimization. Springer-Verlag. 2006
  • R. Fletcher. Practical Methods of Optimization. Wiley. 1987
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN

The course syllabus may change due academic events or other reasons.