Abstract
The success of embedded chaos in metaheuristic algorithms is mainly due to providing good balance between exploration and exploitation for metaheuristics. Comparison of optimization results with algorithms in standard mode and embedded of chaos shows a significant improvement in quality of the metaheuristic algorithms, thus reducing the weight of truss structures. Four chaos metaheuristic algorithms with logistic, Tenet and Gaussian maps are considered to improve the results. Despite truss optimization is severely nonlinear and non-convex, and often has several local optimizations, the use of different scenarios chaos allows the local optimizations to be escaped and global optimization to be achieved.
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