基于黄金工作集多维数值函数极小值算法

摘要

提出一种黄金工作集的多维数值函数极值优化算法。根据工作集元素的贡献度不同并结合黄金分割法将工作集划分为黄金工作集和非黄金工作集。通过保留黄金工作集元素和置换非黄金工作集元素方法，保障工作集中的元素都是最优解，从而达到加速收敛实现算法的优化。通过与人工蜂群算法的进行比较，结果证明该算法在极值收敛上具有明显优势。%This paper describes global optimization algorithm of multi -dimensional numerical function based ongolden selection working set. The working set is divided into a golden selection working set and non - golden se-lection one by the contribution of the working set elements combined with the golden selection. By retaining ele- ments of the golden selection working set and replaceing elements of non - gold one, it can get the optimal solu- tion and achieve speeding up the convergence rate optimization algorithm. Compared with artificial bee colony al-gorithm, simulation result performs better than ABC algorithms in convergence.