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Alternative TitleFactorial-based Particle Swarm Optimization and Its Application to Maritime Moving Target Search
吕进锋; 赵怀慈
Source Publication控制与决策
Indexed ByEI ; CSCD
EI Accession number20190906552524
Contribution Rank1
Keyword析因 粒子群 群智能 优化 海上搜寻 运动目标


Other Abstract

When dealing with complex multimodal function optimization problems, particle swarm optimization (PSO) algorithm trends to trap in local extreme. Aiming at the problem that it is hard for PSO to meet the requirements of maritime moving target search, a factorial-based particle swarm optimization algorithm is presented. This algorithm combines swarm intelligence with factorial experiment design and employs the ideas of randomization and blocking. By designing multi combinations of parameters with different values and calculating the fitness value of each combination, the fitness curves of each parameter can be obtained. This algorithm analyzes the impact of each parameter on the fitness and the interaction between different parameters. Based on that, the shapes of solution spaces can be acquired, and the population can employ different strategies for different parameters to search for the global optima. For the parameters with significant interaction, the population will focus on global search. For the parameters with insignificant interaction, the population will focus on local search. Finally, this paper applies the proposed algorithm to solve maritime moving target search problems. The experimental results show that compared with other algorithms, the proposed algorithm can generate better search plans effectively.

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Document Type期刊论文
Corresponding Author赵怀慈
Recommended Citation
GB/T 7714
吕进锋,赵怀慈. 析因-粒子群算法及其在海上运动目标搜寻中的应用[J]. 控制与决策,2018,33(11):1983-1989.
APA 吕进锋,&赵怀慈.(2018).析因-粒子群算法及其在海上运动目标搜寻中的应用.控制与决策,33(11),1983-1989.
MLA 吕进锋,et al."析因-粒子群算法及其在海上运动目标搜寻中的应用".控制与决策 33.11(2018):1983-1989.
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