Chaotic Local Search-Based Differential Evolution Algorithms for Optimization
Chaotic Local Search-Based Differential Evolution Algorithms for Optimization
复制标题
基于混沌局部搜索的差分进化优化算法
DOI：
10.1109/tsmc.2019.2956121
复制
发表时间：
2021-06-01
影响因子：
8.7
通讯作者：
Zhou, MengChu
中科院分区：
文献类型：
--
作者：
Gao, Shangce;Yu, Yang;Zhou, MengChu
JADE是一种差分进化算法，与其他进化优化算法相比具有很强的竞争力。然而，它存在早熟收敛问题，容易陷入局部最优。本文提出了一种新的JADE变体，通过将混沌局部搜索（CLS）机制到JADE来缓解这个问题。利用混沌的遍历性和非重复性，它可以使种群多样化，从而有机会探索一个巨大的搜索空间。由于其固有的局部开发能力，嵌入CLS可以利用一个小的区域，以改善解决方案得到的JADE。因此，它可以很好地平衡搜索过程中的探索和开发，并进一步提高其性能。研究了四种CLS掺入方案。多个混沌映射是单独的，随机的，随机的，和记忆选择性地纳入CLS。实验和统计分析进行了一组53个基准函数和四个现实世界的优化问题。结果表明，与JADE等现有优化算法相比，该算法具有上级性能。
JADE is a differential evolution (DE) algorithm and has been shown to be very competitive in comparison with other evolutionary optimization algorithms. However, it suffers from the premature convergence problem and is easily trapped into local optima. This article presents a novel JADE variant by incorporating chaotic local search (CLS) mechanisms into JADE to alleviate this problem. Taking advantages of the ergodicity and nonrepetitious nature of chaos, it can diversify the population and thus has a chance to explore a huge search space. Because of the inherent local exploitation ability, its embedded CLS can exploit a small region to refine solutions obtained by JADE. Hence, it can well balance the exploration and exploitation in a search process and further improve its performance. Four kinds of its CLS incorporation schemes are studied. Multiple chaotic maps are individually, randomly, parallelly, and memory-selectively incorporated into CLS. Experimental and statistical analyses are performed on a set of 53 benchmark functions and four real-world optimization problems. Results show that it has a superior performance in comparison with JADE and some other state-of-the-art optimization algorithms.