Optimizacija funkcije evolucijskim algoritmom uz analizu strukture rješenja

undergraduate thesis

• Title (english): Evolutionary Algorithm Based Function Optimization with Solution Structure Analysis
• Author: Nikola Zadravec
• Mentor: Marko Čupić (mentor)
• Committee member: Marko Čupić (predsjednik povjerenstva)
• Committee member: Mladen Karan (član povjerenstva)
• Committee member: Karlo Knežević (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2017-09-13, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Problem optimizacije sveprisutan je u području računarske znanosti kao i
u mnogim drugim područjima. Optimizacijski problem može biti definiran
nad diskretnom domenom, kontinuiranom domenom ili mješavinom obaju
domena. Ovisno o domeni problema, razvijeno je mnoštvo različitih
pristupa za njihovo rješavanje. Dimenzionalnost domene pri tome
predstavlja ograničavajući faktor, pri čemu probleme s
visoko-dimenzijskim domenama često nije moguće rješavati učinkovito.
Jedan od pristupa koji bi kod određenih vrsta problema mogao rezultirati
povećanjem učinkovitosti pronalaska kvalitetnih rješenja jest dinamičko
smanjenje dimenzionalnosti problema na način da se pojedine komponente
domene grupiraju. Primjer takvog pristupa opisan je u radu "Transforming
Evolutionary Search into Higher-Level Evolutionary Search by Capturing
Problem Structure", IEEE Trans. on Evolutionary Computation, October
2014, Vol 18, No 5.

Abstract (english)

The optimization problem is ubiquitous in the field of computer science as well as
in many other areas. The optimization problem can be defined
over a discrete domain, a continuous domain, or a mixture of both domain.
Depending on the domain of the problem, a multitude of different approaches have been developed
for solving them. Domain dimensionality represents a limiting factor, where problems with
high-dimensional domains can often not be effectively addressed.
One approach that could result in certain types of problems
increasing the efficiency of finding quality solutions is dynamic
reducing the dimensionality of the problem in a way that individual components
domains are grouped. An example of such approach is described in "Transforming
evolutionary Search in Higher-Level Evolutionary Search by Capturing
problem Structure ", IEEE Trans. On Evolutionary Computation, October
2014, Vol 18, No 5.

• Keywords: metaheuristika; algoritmi izgrade modela; višerazinsko pretraživanje; Macro-H
• Keywords (english): metaheuristics; model building algorithms; multi-scale search; Macro-H
• Language: croatian
• URN:NBN: urn:nbn:hr:168:300032
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2019-03-14 02:16:38