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• W3143368369 abstract "The symbiotic organisms search (SOS) algorithm is investigated and corrected by removing the benefit factors due to their biased search around the original dot. However, the removal of these benefit factors results in performance that is far inferior to the outstanding performance of the basic SOS algorithm. Accordingly, this paper suggests adopting combination schemes for the mutualistic equations in order to prevent premature convergence, and further recommends adopting lower combination rates for parasitic equations. Combination schemes are found to be not applicable to the commensal equation, as this equation is not greedy. Therefore, this paper proposes two types of combination schemes to improve the corrected SOS version in terms of achieving high early convergence speed, attaining convergence precision at a lower cost, arriving at the convergence plateau at either a lower cost or a higher level of precision, handling tests of composition functions well, and achieving competitive performance on CEC2015 test problems." @default.
• W3143368369 created "2021-04-13" @default.
• W3143368369 creator A5049747408 @default.
• W3143368369 date "2021-09-01" @default.
• W3143368369 modified "2023-09-27" @default.
• W3143368369 title "A corrected and improved symbiotic organisms search algorithm for continuous optimization" @default.
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• W3143368369 doi "https://doi.org/10.1016/j.eswa.2021.114981" @default.
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