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Colliding bodies optimization with Morlet wavelet mutation and quadratic interpolation for global optimization problems
Engineering with Computers Pub Date : 2021-01-04 , DOI: 10.1007/s00366-020-01236-z
Ali Kaveh , Majid Ilchi Ghazaan , Fatemeh Saadatmand

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.



中文翻译:

整体优化问题的Morlet小波突变和二次插值碰撞体优化

本文提出了一种碰撞体优化(CBO)的新方法,其目的是缓解人口多样性的不足,过早的收敛现象以及CBO方法的多样化和强化之间的不平衡。CBO是基于动量和能量定律的两个主体之间的一维碰撞的元启发式算法。通过将CBO与Morlet小波(MW)突变和二次插值(QI)(MWQI-CBO)杂交,设计了该方法。利用Morlet小波突变来改善CBO,以便在找到更好的解决方案时可以更有效地探索搜索空间。此外,利用历史最佳解决方案的二次插值被添加到CBO中以增强开发阶段。定义了两个新参数,以在分散度和强化度之间取得更好的平衡。该算法在24个数学优化问题(包括30个设计变量)中进行了测试,并与标准CBO和一些最新的元启发法进行了比较。此外,研究了五个标准离散和连续结构设计问题的优化设计,这些问题具有强度,稳定性,位移和频率约束等各种约束。结果发现,MWQI-CBO在可靠性,求解精度和收敛速度方面与其他元启发式算法相比具有相当的竞争力。该算法在24个数学优化问题(包括30个设计变量)中进行了测试,并与标准CBO和一些最新的元启发法进行了比较。此外,研究了五个标准离散和连续结构设计问题的优化设计,这些问题具有强度,稳定性,位移和频率约束等各种约束。结果发现,在可靠性,求解精度和收敛速度方面,MWQI-CBO与其他元启发式算法相比具有相当的竞争力。该算法在24个数学优化问题(包括30个设计变量)中进行了测试,并与标准CBO和一些最新的元启发法进行了比较。此外,研究了五个标准离散和连续结构设计问题的优化设计,这些问题具有强度,稳定性,位移和频率约束等各种约束。结果发现,MWQI-CBO在可靠性,求解精度和收敛速度方面与其他元启发式算法相比具有相当的竞争力。

更新日期:2021-01-04
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