An Algorithm for Global Optimization Based on CFO-BFGS

Ruiqi Sun
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Abstract

Evolutionary algorithm has some drawbacks, such as premature convergence. To overcome these problems, this article proposed a hybrid algorithm of Central Force Optimization (CFO) and BFGS method. A new mutation operator are constructed to balance the exploration and exploitation. Several benchmark functions are selected to test the validity of hybrid algorithm. The numerical experiment results show that new algorithm is effective for solving global optimization problems.
基于CFO-BFGS的全局优化算法
进化算法存在着早熟收敛等缺点。为了克服这些问题,本文提出了一种中心力优化(CFO)和BFGS方法的混合算法。构造了一个新的变异算子来平衡勘探和开发。选择了几个基准函数来检验混合算法的有效性。数值实验结果表明,新算法对求解全局优化问题是有效的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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