Differential evolution with preferential interaction network
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F70883521%3A28140%2F17%3A63517319" target="_blank" >RIV/70883521:28140/17:63517319 - isvavai.cz</a>
Alternative codes found
RIV/61989100:27240/17:10238696
Result on the web
<a href="http://dx.doi.org/10.1109/CEC.2017.7969535" target="_blank" >http://dx.doi.org/10.1109/CEC.2017.7969535</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/CEC.2017.7969535" target="_blank" >10.1109/CEC.2017.7969535</a>
Alternative languages
Result language
angličtina
Original language name
Differential evolution with preferential interaction network
Original language description
Population-based metaheuristic optimization methods are built upon an algorithmic implementation of different types of complex dynamic behaviours. The problem-solving strategies they implement are often inspired by various natural and social phenomena whose fundamental principles were adopted for the use in practical search and optimization problems. New insights into complex systems, attained among others within the fields of network science and social network analysis, can be successfully incorporated into the study of evolutionary and swarm methods and used to improve their efficiency. Preferential attachment is a principle governing the growth of many real-world networks. That makes it a natural candidate for the use with network-based models of artificial evolution. Differential evolution is a widely-used evolutionary algorithm valued for its efficiency and versatility as well as simplicity and ease of implementation. In this paper, a variant of differential evolution, guided by an auxiliary model of population dynamics built with the help of the preferential attachment principle, is designed. The efficiency of the proposed approach is analyzed on the CEC 2017 real-parameter optimization benchmark.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings
ISBN
978-150904601-0
ISSN
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e-ISSN
neuvedeno
Number of pages
8
Pages from-to
1916-1923
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Piscataway, New Jersey
Event location
Donostia-San Sebastian
Event date
Jun 5, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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