Competencies and objectives

 

Course context for academic year 2017-18

Ésta es la primera de las asignaturas que constituyen la materia, de tipo obligatorio, denominada "Optimización" que forma parte del módulo fundamental del grado.

La asignatura pretende iniciar al alumno en la metodología científica en la toma de decisiones, casi siempre concernientes a la asignación óptima de recursos escasos, mediante la construcción y resolución de modelos matemáticos. Más concretamente, se hace una discusión pormenorizada de los modelos de uso más frecuente, los de programación lineal. Dicha discusión requiere la introducción de fundamentos de análisis convexo, el estudio de los sistemas de inecuaciones lineales y de sus conjuntos de soluciones -los poliedros-, el desarrollo de algoritmos para la obtención de soluciones óptimas y la evaluación del impacto, en el valor óptimo, de pequeñas variaciones en los datos.

En esta asignatura se utilizan conceptos y resultados vistos previamente en las asignaturas "Álgebra Lineal I", "Álgebra Lineal II" y "Análisis real de varias variables I". 

 

 

Course content (verified by ANECA in official undergraduate and Master’s degrees)

Specific Competences (CE)

  • CE1 : Understand and use mathematical language. Acquire the capacity to enunciate propositions in different fields of Mathematics, to construct demonstrations and transmit the mathematical knowledge acquired.
  • CE11 : Ability to solve academic, technical, financial and social problems using mathematical methods.
  • CE12 : Ability to work in a team, providing mathematical models adapted to the needs of the group.
  • CE14 : Solve qualitative and quantitative problems using previously developed models.
  • CE15 : Recognise and analyse new problems and prepare strategies to resolve them.
  • CE16 : Prepare, present and defend scientific reports both in writing and orally to an audience.
  • CE4 : Know how to abstract the structural properties (of mathematical objects, of observed reality and other contexts) distinguishing them from those that are purely occasional and be able to prove them with demonstrations or refute them with counter-examples, as well as identify errors of incorrect reasoning.
  • CE5 : Propose, analyse, validate and interpret models of simple real-life situations, using the most appropriate mathematical tools for the purpose.
  • CE6 : Solve mathematical problems using basic calculus skills and other techniques, planning their resolution according to the tools available and any time and resource restriction.
  • CE7 : Use computer applications for statistical analysis, numerical calculus and symbolic calculus, graphic visualisation and others to experiment in Mathematics and solve problems.
  • CE8 : Develop programmes that solve mathematical problems using the appropriate computational environment for each particular case.

 

Specific Generic UA Competences

  • CGUA1 : Understand scientific English.
  • CGUA2 : Possess computer knowledge related to the field of study.
  • CGUA3 : Acquire or posses basic ICT (Information and Communication technology) skills and manage the information obtained appropriately.

 

Generic Degree Course Competences

  • CG1 : Develop the capacity for analysis, synthesis and critical reasoning.
  • CG2 : Show the ability for effective and efficient direction/management: entrepreneurial spirit, creativity, organisation, planning, control, decision making and negotiation.
  • CG3 : Resolve problems effectively.
  • CG4 : Show ability for teamwork.
  • CG5 : Commitment to ethics, the values of equality and social responsibility as a citizen and as a professional.
  • CG6 : Learn autonomously.
  • CG7 : Show the ability to adapt to new situations.
  • CG8 : Acquire a permanent concern for quality, the environment, sustainable development and health and safety at work.
  • CG9 : Demonstrate the ability to transmit information, ideas, problems and solutions to both specialist and non-specialist audiences.

 

 

 

Learning outcomes (Training objectives)

No data

 

 

Specific objectives stated by the academic staff for academic year 2017-18

No data

 

 

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General

Code: 25027
Lecturer responsible:
RODRIGUEZ ALVAREZ, MARGARITA
Credits ECTS: 6,00
Theoretical credits: 1,32
Practical credits: 1,08
Distance-base hours: 3,60

Departments involved

  • Dept: MATHEMATICS
    Area: STATISTICS AND OPERATIONS RESEARCH
    Theoretical credits: 1,32
    Practical credits: 1,08
    This Dept. is responsible for the course.
    This Dept. is responsible for the final mark record.

Study programmes where this course is taught