crta
Hrvatska znanstvena Sekcija img
bibliografija
3 gif
 Naslovna
 O projektu
 FAQ
 Kontakt
4 gif
Pregledavanje radova
Jednostavno pretraživanje
Napredno pretraživanje
Skupni podaci
Upis novih radova
Upute
Ispravci prijavljenih radova
Ostale bibliografije
Slični projekti
 Bibliografske baze podataka

Pregled bibliografske jedinice broj: 814275

Časopis

Autori: Bajer, Dražen; Martinović, Goran; Brest, Janez
Naslov: A Population Initialization Method for Evolutionary Algorithms based on Clustering and Cauchy Deviates
Izvornik: Expert systems with applications (0957-4174) 60 (2016); 294-310
Vrsta rada: članak
Ključne riječi: Cauchy deviates ; clustering ; differential evolution ; evolutionary algorithms ; initial population ; mutation
Sažetak:
The initial population of an evolutionary algorithm is an important factor which affects the convergence rate and ultimately its ability to find high quality solutions or satisfactory solutions for that matter. If composed of good individuals it may bias the search towards promising regions of the search space right from the beginning. Although, if no knowledge about the problem at hand is available, the initial population is most often generated completely random, thus no such behavior can be expected. This paper proposes a method for initializing the population that attempts to identify i.e. to get close to promising parts of the search space and to generate (relatively) good solutions in their proximity. The method is based on clustering and a simple Cauchy mutation. The results obtained on a broad set of standard benchmark functions suggest that the proposed method succeeds in the aforementioned which is most noticeable as an increase in convergence rate compared to the usual initialization approach and a method from the literature. Also, insight into the usefulness of advanced initialization methods in higher-dimensional search spaces is provided, at least to some degree, by the results obtained on higher-dimensional problem instances---the proposed method is beneficial in such spaces as well. Moreover, results on several very high-dimensional problem instances suggest that the proposed method is able to provide a good starting position for the search.
Izvorni jezik: ENG
Rad je citiran u
bazama podataka:
Web of Science: Science Citation
Current Contents Citation Index
Web of Science: Science Citation Index Expanded
Scopus
Kategorija: Znanstveni
Znanstvena područja:
Računarstvo
URL Internet adrese: http://www.sciencedirect.com/science/article/pii/S0957417416302287
Broj citata:
Altmetric:
DOI: 10.1016/j.eswa.2016.05.009
URL cjelovitog teksta:
Google Scholar: A Population Initialization Method for Evolutionary Algorithms based on Clustering and Cauchy Deviates
Upisao u CROSBI: Dražen Bajer (drazen.bajer@etfos.hr), 6. Svi. 2016. u 17:42 sati



  Verzija za printanje   za tiskati


upomoc
foot_4