Evolucionāras optimizācijas metodes dinamiskās vidēs
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Latvijas Universitāte
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Abstract
Patreiz evolucionāras optimizācijas algoritmi
tiek strauji attīstīti -- nepārtraukti parādās jaunas
publikācijas ar jauniem pētījumiem vai algoritmu modifikācijām. Dotais darbs cenšas izanalizēt dotās nozares tekošo stāvokli un izdarīt secinājumus par attīstības perspektīvām konkrētajā virzienā. Pētījumi tika veikti balstoties uz dažiem pazīstamiem algoritmiem un uz statistikas, iegūtas no zinātnisko darbu publiskajām datu bāzēm. Rezultātā tika noteikti daži virzieni, kuri prasa papildus uzmanību un pētījumu.
Currently, evolutionary optimization algorithms are expecting fast development -- new algorithms are constantly created, new research papers and algorithm modifications are published. This work makes an attempt to analyse current state of development of given techniques and to estimate potential of development of some research directions. Analysis was based on research of some known algorithms and using statistics gathered from public scientific paper databases. As result, some promising research directions were proposed.
Currently, evolutionary optimization algorithms are expecting fast development -- new algorithms are constantly created, new research papers and algorithm modifications are published. This work makes an attempt to analyse current state of development of given techniques and to estimate potential of development of some research directions. Analysis was based on research of some known algorithms and using statistics gathered from public scientific paper databases. As result, some promising research directions were proposed.