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

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Abstract

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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Authors and Affiliations

  1. School of Civil Engineering, Iran University of Science and Technology, P.O. Box 16846-13114, Tehran, Iran

    Ali Kaveh, Majid Ilchi Ghazaan & Fatemeh Saadatmand

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  1. Ali Kaveh
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  2. Majid Ilchi Ghazaan
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  3. Fatemeh Saadatmand
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Correspondence to Ali Kaveh.

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Kaveh, A., Ilchi Ghazaan, M. & Saadatmand, F. Colliding bodies optimization with Morlet wavelet mutation and quadratic interpolation for global optimization problems. Engineering with Computers 38, 2743–2767 (2022). https://doi.org/10.1007/s00366-020-01236-z

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