Studies > Metaheuristic Algorithms (122 CS)

Metaheuristic Algorithms (122 CS)

Type: For the student's choice

Department: radioelectronic and computer systems

Curriculum

SemesterCreditsReporting
103Setoff

Lectures

SemesterAmount of hoursLecturerGroup(s)
1016Senior Researcher Sokolovskyi B. S.ФеІм-14

Laboratory works

SemesterAmount of hoursGroupTeacher(s)
1016ФеІм-14Senior Researcher Sokolovskyi B. S.

Опис навчальної дисципліни

The course describes the main types of metaheuristic algorithms that can be used to solve a wide range of optimization problems. The main attention is paid to genetic algorithms, in particular, the peculiarities of building genetic algorithms, their structure, and the specifics of genetic operators are considered. Algorithms based on analogy with processes in physical systems (annealing simulation algorithm) and multi-agent biological systems (particle swarm algorithm, bee algorithm, ant algorithm) are also considered.
The discipline aims to develop students’ modern understanding of the essence, types, and operation of metaheuristic algorithms. The ability to apply them to solve optimization problems is the main objective of the discipline.

 

Recommended Literature

Основна література:

  • 1. Кононюк А.Ю. Нейронні мережі і генетичні алгоритми – .:«Корнійчук», 2008. – 446 с.
  • 2. Субботін С. О., Олійник А.О., Олійник О.О. Неітеративні, еволюційні та мультиагентні методи синтезу нечіткологічних і
    нейромережевих моделей. Монографія. – Запоріжжя: ЗНТУ, 2009. – 375c.
  • 3. Luke Sean/ Essential of Metaheuristics. –2009. –235p. Available at http://cs.gmu.edu/~sean/book/metaheuristics/
  • 4. Гуляницький Л. Ф., Мулеса О.Ю. Прикладні методи комбінаторної оптимізації. Навч. посібник. – К.: ВПЦ “Київський університет”, 2016.– 133c.
  • 5. Overview of Metaheuristic Algorithms. S. M. Almufti, Awaz Ahmad Shaban, Rasan Ismael Ali, Jayson A. Dela Fuente. Polaris Global Journal of Scholarly Research and Trends 2023. Vol. 2. PP. 10-32.

Допоміжна література:

  • 6. Talbi El-Ghazari. Metaheuristics. From Design to Implementation. – New Jercey: John &Sons, Inc., 2009. – 618p.
  • 7. Brownlee Jason. Clever Algorithms. Nature-Inspired Programming Recipes. – 2011. – 436p. See also http://www.cleveralgorithms.com
  • 8. Wirsansky Eyal. Hands-On Genetic Algorithms with Python. – Birmingham: Packt, 2020. – 334p.

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