Hybridized optimization algorithms for design of trusses with multiple natural frequency constraints

In this paper, two optimization algorithms are applied for finding the optimal mass of truss structures with natural frequency constraints. The Particle Swarm Optimization with an Aging Leader and Challengers (ALC-PSO) algorithm is the first technique which applies the aging mechanism to particle swarm optimization (PSO) algorithm. The second method is HALC-PSO that transplants harmony search-based mechanism to ALC-PSO as a variable constraint handling approach. In these methods, the leader of the swarm ages and has a limited lifespan which is adaptively tuned according to the leader’s leading power. If a leader shows a strong ability to lead the swarm toward better positions, its lifespan is increased, otherwise the leader gets aged quickly and when its lifespan is exhausted, a new particle emerges to challenge and claim the leadership. Therefore, premature convergence can be prevented in these methods. Five well-known truss mass optimization examples on Layout and size with frequency constraints are presented to demonstrate the viability of the algorithms. This type of problem is highly non-linear and non-convex dynamic optimization problems since mass reduction conflicts with the frequency constraints, especially when they are lower bounded. Numerical results show the robustness and high performance of the ALC-PSO and HALC-PSO algorithms for structural optimization problems with frequency constraints. It is found that the best results are obtained using HALC-PSO algorithm in most of the cases.