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1.

Improved symbiotic organisms search algorithm for solving unconstrained function optimization Pages 361-380 Right click to download the paper Download PDF

Authors: Sukanta Nama, Apu Kumar Saha, Sima Ghosh

DOI: 10.5267/j.dsl.2016.2.004

Keywords: Population based algorithm, Random weighed reflection, Random weighted difference vector, Symbiotic organisms search, Unconstrained optimization

Abstract:
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.
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Journal: DSL | Year: 2016 | Volume: 5 | Issue: 3 | Views: 3172 | Reviews: 0

 

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