- Date: 2020 Jun 19
- Authors: مجتبی شیخی ازغندی
- Keywords: Composite materials,Hybrid meta-heuristic optimization,Colliding bodies optimization, Discrete variable
This study presents a robust hybrid meta-heuristic optimization algorithm by merging
Modified Colliding Bodies Optimization and Genetic Algorithm that is called GMCBO. One
of the inabilities of Colliding Bodies Optimization (CBO) is collapsing into the trap of local
minima and not finding global optima. In this paper, to rectify this weak point, at first, some
modifications are accomplished on the CBO process and then by using the concept of the
genetic algorithm able to enhance the convergence rate, establishing a balance between
the feature exploration and exploitation processes, the increasing power of finding global
optimal design and escaping of local optimal. For evaluating the performance of the
proposed method, the optimal design of laminated composite materials has been
considered. Compare the results of structural analysis with GMCBO and other optimization
methods shows a high convergence rate and its ability to find the global optimal solution
of the proposed algorithm for structural optimization problems.
