Improved symbiotic organisms search algorithm for solving unconstrained function optimization

Recently, Symbiotic Organisms Search (SOS) algorithm is being used for solving complex problems of optimization. This paper proposes an Improved Symbiotic Organisms Search (I-SOS) algorithm for solving different complex unconstrained global optimization problems. In the improved algorithm, a random...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Decision Science Letters Ročník 5; číslo 3; s. 361 - 380
Hlavní autoři:	Nama, Sukanta, Saha, Apu Kumar, Ghosh, Sima
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Growing Science 2016
Témata:	Population based algorithm Random weighed reflection Random weighted difference vector Symbiotic organisms search Unconstrained optimization
ISSN:	1929-5804, 1929-5812
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	Recently, Symbiotic Organisms Search (SOS) algorithm is being used for solving complex problems of optimization. This paper proposes an Improved Symbiotic Organisms Search (I-SOS) algorithm for solving different complex unconstrained global optimization problems. In the improved algorithm, a random weighted reflective parameter and predation phase are suggested to enhance the performance of the algorithm. The performances of this algorithm are compared with the other state-of-the-art algorithms. The parametric study of the common control parameter has also been performed.
ISSN:	1929-5804 1929-5812
DOI:	10.5267/j.dsl.2016.2.004