Master in Computational and Applied Mathematics (Plan: 458 - Estudio: 372)
EPI
Coordinating teacher: MOSCOSO CASTRO, MIGUEL ANGEL
Department assigned to the subject: Mathematics Department
Type: Compulsory
ECTS Credits: 3.0 ECTS
Course: 1º
Semester: 2º
Requirements (Subjects that are assumed to be known)
Students are expected to have a solid background in Linear Algebra and Calculus.
Objectives
- 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
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
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
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The course syllabus may change due academic events or other reasons.
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