Genetski algoritmi i primjene

master's thesis

• Author: Tomislav Droždjek
• Mentor: Nela Bosner (mentor)
• Committee member: Nela Bosner (predsjednik povjerenstva)
• Committee member: Zvonimir Bujanović (član povjerenstva)
• Committee member: Vjeran Hari (član povjerenstva)
• Committee member: Miljenko Marušić (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Mathematics); Zagreb
• Defense date and country: 2015-02-26, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Mathematics

Abstract

Ovaj rad sastoji se od 2 dijela. U prvom dijelu fokus je na definiranju općih pojmova vezanih uz evolucijske algoritme te nekim važnim zapažanjima vezanim uz njihov rad. Nakon toga, koncentriramo se na genetske algoritme, detaljno opisujemo sve bitne dijelove genetskih algoritama, opisujemo njihovu funkciju, način implementacije te navodimo za koje je probleme svaka od tih implementacija najpogodnija. Drugi dio ovog rada fokusira se na demonstraciju rada genetskih algoritama pomoću biomorfa. U ovom dijelu primijenit ćemo genetski algoritam na rješavanje raznih problema iz prostora biomorfa. Koristit ćemo razne kombinacije parametara genetskih algoritama te u ovisnosti o kompleksnosti problema proučiti kako oni utječu na izvedbu samog algoritma.

Abstract (english)

This work consists of 2 major parts. In the first part, the focus is on defining key concepts of evolutionary algorithms, making some important observations regarding the way they obtain solutions and the way they function in general. Subsequently, genetic algorithms are studied in more detail, all their parts are thoroughly described, as well as their role in the algorithm itself. Also, different implementations suitable for various problems are described. In the second part, an example genetic algorithm is applied to different problems from the biomorph space, varying in difficulty and complexity. The algorithm is executed with various parameters, and the obtained results are used in order to study how the algorithm solves diverse problems depending on the chosen parameters.

• Keywords: evolucijski algoritmi; genetski algoritmi; biomorf
• Keywords (english): evolutionary algorithms; genetic algorithms; biomorph
• Language: croatian
• URN:NBN: urn:nbn:hr:217:402481
• Study programme: Title: Applied Mathematics; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra matematike (magistar/magistra matematike)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2019-01-09 11:48:01