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差分扰动的堆优化算法 被引量:6

Differential disturbed heap-based optimizer
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摘要 针对堆优化算法(HBO)在解决复杂问题时存在搜索能力不足和搜索效率低等缺陷,提出一种差分扰动的HBO--DDHBO。首先,提出一种随机差分扰动策略更新最优个体的位置,以解决HBO没有对其更新从而导致的搜索效率低的问题;其次,使用一种最优最差差分扰动策略更新最差个体的位置,以强化其搜索能力;然后,采用一种多层差分扰动策略更新一般个体的位置,以强化多层个体之间的信息交流,并提高搜索能力;最后,针对原更新模型在搜索初期获得有效解概率低的问题,提出一种基于维的差分扰动策略更新其他个体的位置。在大量CEC2017复杂函数上的实验结果表明,与HBO相比,DDHBO在96.67%的函数上具有更好的优化性能,更少的平均运行时间(3.4450s);与WRBBO(Worst opposition learning and Random-scaled differential mutation Biogeography-Based Optimization)、DEBBO(Differential Evolution and Biogeography-Based Optimization)和HGWOP(Hybrid PSO and Grey Wolf Optimizer)等先进算法相比,DDHBO也具有显著的优势。 In order to solve the problems,such as insufficient search ability and low search efficiency of Heap-Based optimizer(HBO)in solving complex problems,a Differential disturbed HBO(DDHBO)was proposed.Firstly,a random differential disturbance strategy was proposed to update the best individual’s position to solve the problem of low search efficiency caused by not updating of this individual by HBO.Secondly,a best worst differential disturbance strategy was used to update the worst individual’s position and strengthen its search ability.Thirdly,the ordinary individual’s position was updated by a multi-level differential disturbance strategy to strengthen information communication among individuals between multiple levels and improve the search ability.Finally,a dimension-based differential disturbance strategy was proposed for other individuals to improve the probability of obtaining effective solutions in initial stage of original updating model.Experimental results on a large number of complex functions from CEC2017 show that compared with HBO,DDHBO has better optimization performance on 96.67%functions and less average running time(3.4450s),and compared with other state-of-the-art algorithms,such as Worst opposition learning and Random-scaled differential mutation Biogeography-Based Optimization(WRBBO),Differential Evolution and Biogeography-Based Optimization(DEBBO),Hybrid Particle Swarm Optimization and Grey Wolf Optimizer(HGWOP),etc.,DDHBO also has significant advantages.
作者 张新明 温少晨 刘尚旺 ZHANG Xinming;WEN Shaochen;LIU Shangwang(College of Computer and Information Engineering,Henan Normal University,Xinxiang Henan 453007,China;Engineering Lab of Intelligence Business and Internet of Things of Henan Province(Henan Normal University),Xinxiang Henan 453007,China)
出处 《计算机应用》 CSCD 北大核心 2022年第8期2519-2527,共9页 journal of Computer Applications
基金 河南省高等学校重点科研项目(19A520026)。
关键词 优化算法 元启发式算法 堆优化算法 全局最优解 差分扰动 optimization algorithm meta-heuristic algorithm Heap-Based Optimizer(HBO) global best solution differential disturbance
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