基于缩放因子和协作算子的肾脏算法
Kidney-Inspired Algorithm Based on Scaling Factor and Cooperative Operator
DOI: 10.12677/CSA.2018.84052, PDF,  被引量    科研立项经费支持
作者: 柯 琪*, 温洁嫦：广东工业大学应用数学学院，广东 广州
关键词: 最优化；KA算法；协作算子；缩放因子；Optimization； Kidney-Inspired Algorithm； Cooperative Operator； Scaling Factor
摘要: 本文研究优化问题中的肾脏算法(Kidney-inspired algorithm, KA)，对肾脏算法(KA)存在的缺陷进行了改进，并在许多优化问题中显示出不错的效果。针对KA算法在某些函数上寻优精度低、且容易过早地陷入局部最优的问题。引入了协作算子来增加种群多样性，并在重吸收更新公式上加入缩放因子，达到跳出局部最优解的目的。实验对比说明，改进的算法是一个有效的稳定算法，具有更高的求解精度和更快的收敛速度。
Abstract: In this paper, the kidney-inspired algorithm (KA) is studied in the optimization problem. It im-proves the defects in the kidney algorithm (KA) and shows good results in many optimization problems. For the KA algorithm, there is a problem that the search accuracy is low and it is easy to fall into the local optimum early on some functions. A cooperative operator was introduced to increase the diversity of the population and a scaling factor was added to the reabsorption update formula to achieve the goal of jumping out of the local optimal solution. Experimental comparison shows that the improved algorithm is an effective stable algorithm with higher accuracy and faster convergence speed.
文章引用：柯琪, 温洁嫦. 基于缩放因子和协作算子的肾脏算法[J]. 计算机科学与应用, 2018, 8(4): 472-479. https://doi.org/10.12677/CSA.2018.84052

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