Guías Docentes Electrónicas
1. General information
ECTS credits:
2351 -
Academic year:
602 -
Main language:
Second language:
Use of additional languages:
English Friendly:
Web site:
Lecturer: ALBERTO DONOSO BELLON - Group(s): 20 
Phone number
Office hours
Se informará a comienzo del curso

2. Pre-Requisites

Previous knowledge of multivariable calculus, linear algebra, and ordinary and partial differential equations is required

3. Justification in the curriculum, relation to other subjects and to the profession

This course pretends to be a first contact to the field of optimization through mathamatical programming, calculus of variations and optimal control. It will be of great help not only for students with mathematical background but also for physicians and engineers interested in modeling some problems as optimization ones.

4. Degree competences achieved in this course
Course competences
Code Description
CB06 Possess and understand knowledge that provides a basis or opportunity to be original in the development and / or application of ideas, often in a research context.
CB07 Apply the achieved knowledge and ability to solve problems in new or unfamiliar environments within broader (or multidisciplinary) contexts related to the area of study
CB08 Be able to integrate knowledge and face the complexity of making judgments based on information that, being incomplete or limited, includes reflections on social and ethical responsibilities linked to the application of knowledge and judgments
CB09 Know how to communicate the conclusions and their supported knowledge and ultimate reasons to specialized and non-specialized audiences in a clear and unambiguous way
CB10 Have the learning skills which allow to continue studying in a self-directed or autonomous way
CE03 Have the ability to build and develop advanced mathematical reasoning, and delve into the different fields of mathematics
CG05 Gain the ability to develop a scientific research work independently and in its entirety. Be able to search and assimilate scientific literature, formulate hypotheses, raise and develop problems and draw conclusions from the obtained results
CT03 Develop critical reasoning and the ability to criticize and self-criticize
5. Objectives or Learning Outcomes
Course learning outcomes
Be able to apply the acquired knowledge to treat different non-linear differential equations
To conceive the need for weak derivation in the environment of Sobolev spaces
Become familiar with the different techniques of Nonlinear Analysis
Additional outcomes
Not established.
6. Units / Contents
  • Unit 1: Linear programming
  • Unit 2: Non-linear programming
  • Unit 3: Calculus of Variations
  • Unit 4: Optimal control
  • Unit 5: Variational methods for non-linear analysis
7. Activities, Units/Modules and Methodology
Training Activity Methodology Related Competences ECTS Hours As Com R Description
Class Attendance (theory) [ON-SITE] Lectures 3 75 N N N
Writing of reports or projects [OFF-SITE] Assessment tests 3 75 Y Y Y
Total: 6 150
Total credits of in-class work: 3 Total class time hours: 75
Total credits of out of class work: 3 Total hours of out of class work: 75
As: Assessable training activity
Com: Training activity of compulsory overcoming
R: Rescheduling training activity
8. Evaluation criteria and Grading System
  Grading System  
Evaluation System Face-to-Face Self-Study Student Description
Assessment of problem solving and/or case studies 15.00% 15.00% Exercises to support the main concepts
Theoretical papers assessment 70.00% 70.00% Oral presentation of a case study
Progress Tests 15.00% 15.00% Regular tests
Total: 100.00% 100.00%  

Evaluation criteria for the final exam:
Evaluation criteria not defined
Specifications for the resit/retake exam:
Evaluation criteria not defined
Specifications for the second resit / retake exam:
Evaluation criteria not defined
9. Assignments, course calendar and important dates
Not related to the syllabus/contents
Hours hours
Writing of reports or projects [AUTÓNOMA][Assessment tests] 75

Unit 1 (de 5): Linear programming
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 15

Unit 2 (de 5): Non-linear programming
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 15

Unit 3 (de 5): Calculus of Variations
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 15

Unit 4 (de 5): Optimal control
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 15

Unit 5 (de 5): Variational methods for non-linear analysis
Activities Hours
Class Attendance (theory) [PRESENCIAL][Lectures] 15

Global activity
Activities hours
10. Bibliography and Sources
Author(s) Title Book/Journal Citv Publishing house ISBN Year Description Link Catálogo biblioteca
Pablo Pedregal Introduction to Optimization Springer 0-387-40398-1 2004 Ficha de la biblioteca

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