Centroid-based Initialized JADE for global optimization

Rashida Adeeb Khanum, Muhammad Asif Jan
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引用次数: 14

Abstract

JADE is a recent adaptive version of nature inspired algorithm, Differential Evolution (DE). It has shown considerable performance improvement on a set of well studied benchmark functions. This paper studies whether the performance of JADE can be improved further by changing its random population initialization with centroid based population initialization. The new algorithm is known as Centroid-based Initialized JADE (ciJADE). ciJADE not only initialize JADE from centroids of the random parents, it also reflects the worst ten percent of the centroids population. ciJADE is tested on fourteen CEC2005 competition test problems. Experimental results show that ciJADE has significantly improved the performance of JADE on various problems.
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基于质心的初始化JADE进行全局优化
JADE是受自然启发的微分进化算法(Differential Evolution, DE)的最新自适应版本。它在一组经过充分研究的基准函数上显示出相当大的性能改进。本文研究了将JADE的随机种群初始化改为基于质心的种群初始化,是否可以进一步提高JADE的性能。新算法被称为基于质心的初始化JADE (ciJADE)。ciJADE不仅从随机亲本的质心初始化JADE,还反映了质心种群中最差的10%。ciJADE通过了14道CEC2005竞赛测试题。实验结果表明,ciJADE显著提高了JADE在各种问题上的性能。
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