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Advanced Mathematics for Informatics - System Optimisation

Felsőbb matematika informatikusoknak - Rendszeroptimalizálás
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
Subject name (Hungarian, English)
Felsőbb matematika informatikusoknak - Rendszeroptimalizálás
Advanced Mathematics for Informatics - System Optimisation
Subject code BMEVISZMA02
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 4 0 0
type (linked/independent)
Assessment type vizsga
Credits 4
Subject coordinator
DR. Szeszlér Dávid
position: egyetemi docens
Responsible department
Számítástudományi és Információelméleti Tanszék
Faculty Villamosmérnöki és Informatikai Kar
Subject website http://cs.bme.hu/rendszeropt
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme
Linear programming. Methods of solution, Farkas' lemma,
duality, integer programming, branch and bound, totally unimodular
matrices.
Matroid theory. Basic notions, greedy algorithm, duality, minors,
direct sum, algorithms, Tutte's and Seymour's theorems, rank function,
matroid matching.
Approximation algorithms. Additive and relative error, examples.
Scheduling algorithms. Types, algorithms of Hu, Coffman and Graham.
Reliable network design. Local edge connectivity, edge connectivity
number, algorithms of Nagamochi and Ibaraki, Karger, Khuller and
Vishkin, Cheriyan and Thurimella, Plesnik.
Applications in electrical networks and statics. Kichhoff's theorems,
rigidity of frameworks.
The subject introduces some areas of operations research and combinatorial optimization. Besides covering the most relevant algorithms and methods and their limits, it also aims at giving a glimpse into some of their engineering applications. Thus the subject also covers some general algorithmic approaches like linear and integer programming and matroid theory. Furthermore, the course aims at extending and deepening the knowledge formerly provided by the Introduction to the Theory of Computing 1 and 2 and the Theory of Algorithms subjects of the BSc degree program in Software Engineering.

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

4 hours of lecture per week

Tanulástámogató anyagok

Online források
Foulds, L. R. (2012). Combinatorial optimization for undergraduates. Springer Science & Business Media.

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
nincs
General rules
Requirements: Signature: 1 midterm during the semester the result of which has to be at least 40%. Final: Oral exam. Additional possibilities: 2 occasions for retaking the midterm will be provided (the second one in the week preceding the exam period).
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses

Not provided.

Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.