A hybrid CBO–PSO algorithm for optimal design of truss structures with dynamic constraints

• A new hybrid CBO–PSO algorithm is presented by adding positive properties of the PSO algorithm to the CBO.
• The CBO is a recently developed meta-heuristic algorithm which does not use the internal parameter and memory in its formulation.
• In the CBO–PSO the memory of the PSO is added to the CBO to improve the performance of the latter algorithm.
• The new algorithm is compared to other advanced meta-heuristic methods to illustrate the effectiveness.

The vibration domain of structures can be reduced by imposing some constraints on their natural frequencies. For this purpose optimal design of structures under frequency constraints is required which involves highly non-linear and non-convex problems. In this paper an efficient hybrid algorithm is developed for solving such optimization problems. This algorithm utilizes the recently developed colliding bodies optimization (CBO) algorithm as the main engine and uses the positive properties of the particle swarm optimization (PSO) algorithm to increase the efficiency of the CBO. The distinct feature of the present hybrid algorithm is that it requires no parameter tuning. The CBO is known for being parameter independent, and avoiding the use of the traditional penalty method to handle the constraints upholds this property. Two mathematical constrained functions taken from the literature are studied to verify the performance of the algorithm. The algorithm is then applied to optimize truss structures with frequency limitations. The numerical results demonstrate the efficiency of the presented algorithm for this class of problems.

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