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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Veröffentlicht in:Decision Science Letters Jg. 5; H. 3; S. 361 - 380
Hauptverfasser: Nama, Sukanta, Saha, Apu Kumar, Ghosh, Sima
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Growing Science 2016
Schlagworte:
Population based algorithm
Random weighed reflection
Random weighted difference vector
Symbiotic organisms search
Unconstrained optimization
ISSN:1929-5804, 1929-5812
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Zusammenfassung: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