A Hybrid Symbiosis Organisms Search algorithm and

Authors: Sukanta Nama Apu Kumar Saha Sima Ghosh

Publish Date: 2016/06/10

Volume: 9, Issue: 3, Pages: 261-280

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Abstract

In this paper a new hybrid algorithm Hybrid Symbiosis Organisms Search HSOS has been proposed by combining Symbiosis Organisms Search SOS algorithm with Simple Quadratic Interpolation SQI The proposed algorithm provides more efficient behavior when dealing with realworld and large scale problems To verify the performance of this suggested algorithm 13 Thirteen well known benchmark functions CEC2005 and CEC2010 special session on realparameter optimization are being considered The results obtained by the proposed method are compared with other stateoftheart algorithms and it was observed that the suggested approach provides an effective and efficient solution in regards to the quality of the final result as well as the convergence rate Moreover the effect of the common controlling parameters of the algorithm viz population size number of fitness evaluations number of generations of the algorithm are also being investigated by considering different population sizes and the number of fitness evaluations number of generations Finally the method endorsed in this paper has been applied to two real life problems and it was inferred that the output of the proposed algorithm is satisfactoryThe authors would like to thank Dr PN Suganthan for providing the source code of some PSO variants The authors would also like to express their sincere thanks to the referees and editor for their valuable comments and suggestions which has proved to be an immense help in the improvement of the paper

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