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...

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Bibliographic Details
Published in:	Decision Science Letters Vol. 5; no. 3; pp. 361 - 380
Main Authors:	Nama, Sukanta, Saha, Apu Kumar, Ghosh, Sima
Format:	Journal Article
Language:	English
Published:	Growing Science 2016
Subjects:	Population based algorithm Random weighed reflection Random weighted difference vector Symbiotic organisms search Unconstrained optimization
ISSN:	1929-5804, 1929-5812
Online Access:	Get full text
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Summary:	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