Abstract
Article history: Received October 25, 2015 Received in revised format: February 12, 2016 Accepted February 22, 2016 Available online Februray 22 2016 Recently, Symbiotic Organisms Search (SOS) algorithm is being used for solving complex problems of optimization. This paper proposes an Improved Symbiotic Organisms Search (ISOS) 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. Growing Science Ltd. All rights reserved. 6 © 201
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