Randomization and Complex Networks for Meta-Heuristic Algorithms

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F18%3A10241926" target="_blank" >RIV/61989100:27240/18:10241926 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/70883521:28140/18:63521808

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007/978-3-662-55663-4_9" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-662-55663-4_9</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Randomization and Complex Networks for Meta-Heuristic Algorithms

Popis výsledku v původním jazyce

This chapter deals with the hybridization of the chaos driven heuristics concept and complex networks framework for meta-heuristic. This research aims on the experimental investigations on the time development and influence of different randomization types, different strategies for Differential Evolution (DE) through the analysis of complex network as a record of population dynamics and indices selection. The population is visualized as an evolving complex network, which exhibits non-trivial features such as adjacency graph, centralities, clustering coefficient and other attributes showing efficiency of the network. Experiments were performed for different DE strategies, several different randomization types and simple test functions.

Název v anglickém jazyce

Randomization and Complex Networks for Meta-Heuristic Algorithms

Popis výsledku anglicky

This chapter deals with the hybridization of the chaos driven heuristics concept and complex networks framework for meta-heuristic. This research aims on the experimental investigations on the time development and influence of different randomization types, different strategies for Differential Evolution (DE) through the analysis of complex network as a record of population dynamics and indices selection. The population is visualized as an evolving complex network, which exhibits non-trivial features such as adjacency graph, centralities, clustering coefficient and other attributes showing efficiency of the network. Experiments were performed for different DE strategies, several different randomization types and simple test functions.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Evolutionary Algorithms, Swarm Dynamics and Complex Networks

ISBN

978-3-662-55661-0

Počet stran výsledku

18

Strana od-do

177-194

Počet stran knihy

312

Název nakladatele

Springer, Berlin, Heidelberg

Místo vydání

Germany

Kód UT WoS kapitoly

—