Abstract
This paper introduces a novel optimization algorithm, group search optimization (GSO) algorithm and its implementation method is presented in detail. The GSO is used to investigate the planar and space truss structures with continuous variables and is tested by two truss optimization problems. The optimization results are compared with that of the particle swarm optimization (PSO) algorithm, the particle swarm optimization with passive congregation (PSOPC) and the heuristic particle swarm optimizer (HPSO) algorithm. Results from the two tested cases illustrate the ability of the GSO algorithm to find the optimal results, which are better than that of the PSO and PSOPC, while are at the same level of that of HPSO optimization method. Meanwhile, the results also show that the GSO algorithm maintains a preferable convergence accuracy among these four algorithms
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