Applied module: Optimization

Mathematics BSc
Course description
2013.

Eötvös Loránd University
Faculty of Science
Institute of Mathematics

All courses
Core courses
- Algebra, number theory
- Analysis
- Geometry
  - Geometry 1
- Discrete mathematics
  - Discrete mathematics 1
  - Discrete mathematics 2
- Elementary mathematics
  - Elementary mathematics 1
- Informatics
  - Prog. fundamentals
Pure mathematics
- Algebra, number theory
- Analysis
  - Analysis 3
  - Analysis 4
  - Applied analysis
    - Numerical analysis
    - Appl. anal. comp.
  - Differential equations
    - Differential equations
    - Partial diff. equations
  - Topology
    - Introduction
    - Algebraic topology
  - Complex analysis
  - Functional analysis
  - Function series
- Geometry
- Operations research
  - Operations research 1
  - Operations research 2
- Probability theory
- Informatics
- Computer science
- Foundations of math.
  - Set theory
  - Mathematical logic
Applied mathematics
- Analysis
  - Analysis 3
  - Analysis 4
  - Analysis 5
  - Applied analysis
  - Differential equations
    - Differential equations
    - Partial diff. equations
  - Complex analysis
  - Functional analysis
- Geometry
- Operations research
  - Operations research 1
  - Operations research 2
- Probability theory
- Applied modules
- Informatics
- Algorithms
- Algebra
- Elementary mathematics
  - Elementary mathematics 2
  - Elementary mathematics 3
- Foundations of math.
BSc: general information
Studies

Hours lect+pc	Credits lect+pc	Assessment	Specialization	Course code lect/pc	Semester	Status
2 + 2	2 + 3	exam + term grade	applied math.	mm1c1md5a mm1c2md5a	5	optional

Course coordinator

Alpár Jüttner
Department of Operations Research
Institute of Mathematics

Strong	Weak	Prerequisites
Practice class
Practice class		Strong: Operations research1L-p (mm1c1op3m) or Operations research1L-a (mm1c1op3a)
Lecture
Lecture		Weak: practice class

Remarks

Syllabus designed by:

Alpár Jüttner, Department of Operations Research, Institute of Mathematics.

Prerequisites

Graph theory, linear programming.

Literature

R. K. Ahuja, T. L. Magnanti, J. B. Orlin: Network Flows: theory, algorithms, and applications. 1993.
D-Z. Du, P. M. Pardalos: Network Optimization Problems: Algorithms, Applications and Complexity. Singapore: World Scientific, 1993.
M. S. Daskin: Network and discrete location: models, algorithms, and applications. Wiley, 2011.
W. J. Cook, W. H. Cunningham, W. R. Pulleyblank, A. Schrijver: Combinatorial Optimization (Vol. 33). Wiley, 2011.

Syllabus

Implementation details of shortest path, network flow and matching algorithms. Fractional optimization. Column generation and Lagrange relaxation techniques; their application to resource constrained optimization, multicommodity flow, packing and timetabling problems.

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