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Title:
UPORABA ŠAHOVSKEGA SISTEMA RANGIRANJA ZA PRIMERJAVO EVOLUCIJSKIH ALGORITMOV VEČKRITERIJSKE OPTIMIZACIJE
Authors:
ID
Ravber, Miha
(
Author
)
ID
Črepinšek, Matej
(
Mentor
)
More about this mentor...
Files:
MAG_Ravber_Miha_2015.pdf
(15,92 MB)
MD5: 201BAE2CBAA27FA57A7855466B93E83A
Language:
Slovenian
Work type:
Master's thesis/paper
Typology:
2.09 - Master's Thesis
Organization:
FERI - Faculty of Electrical Engineering and Computer Science
Abstract:
Magistrsko delo obravnava primerjavo evolucijskih algoritmov večkriterijske optimizacije z uporabo šahovskega rangiranja. Na začetku je opisano šahovsko rangiranje in osnovni pojmi večkriterijske optimizacije. Prikazana je nadgradnja orodja EARS (ang. Evolutionary Algorithms Rating System), ki omogoča ocenjevanje uspešnosti evolucijskih algoritmov za enokriterijsko optimizacijo. Predstavljena je implementacija primernih primerjalnih funkcij in nabora preizkusnih problemov. Prav tako so predstavljeni tudi nekateri bolj znani evolucijski algoritmi večkriterijske optimizacije, ki smo jih vključili v orodje EARS. Na koncu so prikazani rezultati in primerjava rezultatov orodja EARS z drugimi metodami.
Keywords:
Evolucijski algoritmi
,
večkriterijsko optimiranje
,
sistem rangiranja.
Place of publishing:
[Maribor
Publisher:
M. Ravber
Year of publishing:
2015
PID:
20.500.12556/DKUM-54156
UDC:
004.421(043.2)
COBISS.SI-ID:
19094038
NUK URN:
URN:SI:UM:DK:0KPV5AXC
Publication date in DKUM:
14.10.2015
Views:
1850
Downloads:
204
Metadata:
Categories:
KTFMB - FERI
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Secondary language
Language:
English
Title:
A CHESS RATING SYSTEM FOR THE COMPARISON OF MULTI-OBJECTIVE EVOLUTIONARY ALGORITHMS
Abstract:
In this thesis the comparison of multi-objective evolutionary algorithms using chess ranking is presented. First, the chess ranking and the basic concepts of multi-objective optimization are described. Then the upgrade of EARS (Evolutionary Algorithms Rating System), which enables the assessment of the performance of evolutionary algorithms for single-objective optimization is presented. The implementation of appropriate comparator functions and a set of test problems is also presented. Some of more well-known evolutionary algorithms of multi-objective optimization which were included in EARS are shown. Finally, the results and the comparison of EARS results with other methods are outlined.
Keywords:
Evolutionary algorithms
,
multi-objective optimization
,
rating system.
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