A hybrid genetic modified colliding bodies optimization algorithm for design of structures with multi loads

This paper presents a new hybrid optimization method with combining colliding bodies optimization (CBO) and genetic algorithm (GMCBO). One of the weaknesses of colliding bodies optimization is falling into the trap of local optimal and not finding of global optima. In this paper, to overcome this weak point, at first, some modifications are done on CBO process and then by using the concept of genetic algorithm able to enhance of convergence rate, increasing power of finding global optimal design and escaping of local optimal. For evaluating the performance of the proposed method, the optimal design of several benchmark truss structures has been discussed. Compare the results of the structural analysis with GMCBO and other optimization methods such as colliding bodies optimization, genetic algorithm, harmony search, and heuristic particle swarm optimization method shows high convergence rate and its ability to find the global optimal solution of the proposed algorithm for structural optimization problems.