Subject Datasheet

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Budapest University of Technology and Economics
Faculty of Transportation Engineering and Vehicle Engineering
1. Subject name Algorithm Design
2. Subject name in Hungarian Algoritmusok tervezése
3. Code BMEKOKAM326 4. Evaluation type mid-term grade 5. Credits 5
6. Weekly contact hours 2 (10) Lecture 0 (0) Practice 2 (11) Lab
7. Curriculum
Logistics Engineering MSc (L)
8. Role
Mandatory (mc) at Logistics Engineering MSc (L)
9. Working hours for fulfilling the requirements of the subject 150
Contact hours 56 Preparation for seminars 18 Homework 30
Reading written materials 34 Midterm preparation 12 Exam preparation 0
10. Department Department of Control for Transportation and Vehicle Systems
11. Responsible lecturer Dr. Bécsi Tamás
12. Lecturers Dr. Bécsi Tamás
13. Prerequisites  
14. Description of lectures
Algorithm design. Numerical complexity. The O notation. Efficiency, calculation, and memory requirements for algorithms. Algorithm descriptive tools: flowchart, structogram, pseudo code. Elements of structured programming, its relationship with the design of algorithms.
In addition, the methods of designing algorithms and their optimization are presented. The theoretical background of the subject is illustrated with examples from the field of logistics.
Algorithm design paradigms: algorithm reduction, divide-and-conquer, dynamic programming, "greedy" algorithm, backtracking, etc.
Designing data structures from an algorithmic point of view. Lists, tree structure, graphs. Sorting, searching algorithms. Route Choice and Traveling Salesman problems.
15. Description of practices
16. Description of labortory practices
In the course of laboratory tasks the implementation questions of the theoretical material of the lecture are presented. In addition, students implement algorithms in a development environment of their own choice.
17. Learning outcomes
A. Knowledge
  • knows the concept of numerical complexity
  • knows different basic algorithm design approaches
  • knows basic data structures
B. Skills
  • can independently evaluate the complexity of an algorithm
  • can design algorithms for well-defined tasks
C. Attitudes
  • is interested in modern IT solutions
  • capable of algorithmic thinking that can be applied in other areas
D. Autonomy and Responsibility
  • is able to consult in a team in algorithmic and programming tasks, to make independent decision
18. Requirements, way to determine a grade (obtain a signature)
Two midterm exams. The final grade is the rounded average of the exams.
19. Opportunity for repeat/retake and delayed completion
One midterm exam can be retried in the delayed completion period.
20. Learning materials
Lecture Notes
Effective date 10 October 2019 This Subject Datasheet is valid for Inactive courses