4.7 Article

Colliding bodies optimization with Morlet wavelet mutation and quadratic interpolation for global optimization problems

期刊

ENGINEERING WITH COMPUTERS
卷 38, 期 3, 页码 2743-2767

出版社

SPRINGER
DOI: 10.1007/s00366-020-01236-z

关键词

Colliding bodies optimization; Quadratic interpolation; Wavelet mutation; Structural optimization; Discrete and continuous optimization

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This paper introduces a new variant of colliding bodies optimization method MWQI-CBO, which improves the CBO algorithm by combining Morlet wavelet and quadratic interpolation to achieve better solutions. Through testing on 24 mathematical problems and five structural design problems, it is found that MWQI-CBO is competitive with other meta-heuristic algorithms in terms of reliability, accuracy, and convergence speed.
This paper represents a new variant of colliding bodies optimization (CBO) and the objective is to alleviate the lack of population diversity, premature convergence phenomenon, and the imbalance between the diversification and intensification of the CBO method. The CBO is a meta-heuristic algorithm based on momentum and energy laws in a one-dimensional collision between two bodies. The proposed method is designed by hybridization of the CBO with Morlet wavelet (MW) mutation and quadratic interpolation (QI) (MWQI-CBO). The Morlet wavelet mutation is employed to improve the CBO so that it can explore the search space more effectively on reaching a better solution. Besides, quadratic interpolation that utilized historically best solution is added to CBO to enhance the exploitation phase. Two new parameters are defined to have a better balance between the diversification and the intensification inclinations. The proposed algorithm is tested in 24 mathematical optimization problems including 30 design variables and compared with standard CBO and some state-of-art metaheuristics. Besides, the optimal design of five standard discrete and continuous structural design problems with various constraints such as strength, stability, displacement, and frequency constraints are studied. It is found that MWQI-CBO is quite competitive with other meta-heuristic algorithms in terms of reliability, solution accuracy, and convergence speed.

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