An evolutionary symbiotic organisms search for multiconstraint truss optimization under free vibration and transient behavior. (October 2021) - Nguyen-Van, Sy; Nguyen, Khoa T.; Dang, Khanh D.; Nguyen, Nga T.T.; Lee, Seunghye; Lieu, Qui X.
Highlights: A novel evolutionary symbiotic organisms search algorithm is proposed. The proposed method has novel hybrid mutations of differential evolution and symbiotic organisms search. The present paradigm is of a better balance for both exploration and exploitation abilities. The suggested approach is first validated on truss optimization with free vibration and transient behavior. The developed algorithm dramatically ameliorates the convergence speed, yet still providing high-quality optimal solutions. Abstract: In this paper, an evolutionary symbiotic organisms search algorithm as a hybridization of differential evolution and symbiotic organisms search is developed for shape and size optimization of truss structures with free vibration and transient behavior under multiple constraints. For that aim, a mutation operator combined by two global differential evolution operators and a novel symbiotic organisms search operator is proposed to reinforce the exploration ability of the proposed algorithm. This newly suggested symbiotic organisms search operator is relied upon the symbiotic relationship in such a way that an arbitrary organism can receive benefits from both mutualisms and commensalisms. A threshold is automatically integrated into the mutation step to switch from the exploration capability to the exploitation one. In addition, an elitist scheme is applied to the selection phase to purify the most potential candidates for the next symbiotic ecosystem. Accordingly, the present algorithm can result in a high-quality optimal solution with a better convergence evolution. 26 mathematical functions and 7 well-known benchmark problems regarding size and shape truss optimization under multiple constraints are tested to verify the effectiveness of the proposed methodology. Obtained outcomes have indicated that the developed algorithm outperforms both original algorithms and many existing approaches in the literature. To further illustrate the ability of the proposed paradigm, two among the above five examples under transient excitations with strength, displacement, and buckling constraints are then optimized.