Abstract

To improve the searching effectiveness of the harmony search (HS) algorithm, an enhanced harmony search algorithm with circular region perturbation (EHS_CRP) is proposed in this paper. In the EHS_CRP algorithm, a global and local dimension selection strategy is designed to accelerate the search speed of the algorithm. A selection learning operator based on the global and local mean level is proposed to improve the balance between exploration and exploitation. Circular region perturbation is employed to avoid the algorithm stagnation and get a better exploration region. To assess performance, the proposed algorithm is compared with 10 state-of-the-art swarm intelligent approaches in a large set of global optimization problems. The simulation results confirm that EHS_CRP has a significant advantage in terms of accuracy, convergence speed, stability and robustness. Moreover, EHS_CRP performs better than other tested methods in engineering design optimization problems. Thus, the EHS_CRP algorithm is a viable and reliable alternative for some difficult and multidimensional real-world problems.

中文翻译：

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具有圆形区域摄动的增强和声搜索算法用于全局优化问题

摘要

为了提高和声搜索算法的搜索效率，提出了一种具有圆形区域摄动的增强和声搜索算法。在EHS_CRP算法中，设计了全局和局部维选择策略以加快算法的搜索速度。提出了一种基于全局和局部均值水平的选择学习算子，以改善勘探与开发之间的平衡。利用圆形区域摄动来避免算法停滞并获得更好的探测区域。为了评估性能，将所提出的算法与10种最新的群体智能方法在大量全局优化问题中进行了比较。仿真结果证实，EHS_CRP在准确性，收敛速度，稳定性和鲁棒性。此外，在工程设计优化问题中，EHS_CRP的性能优于其他经过测试的方法。因此，EHS_CRP算法是解决某些难题和多维现实世界问题的可行且可靠的替代方法。