一种新的随机优化方法:海豚群优化算法

IF 0.8 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

International Journal of Computational Intelligence and Applications Pub Date : 2016-06-20 DOI:10.1142/S1469026816500115

Wang Yong, Wang Tao, Zhang Cheng-zhi, Huang Hua-Juan

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引用次数: 16

摘要

提出了一种新型的基于自然启发的群体智能优化算法——海豚群优化算法(DSOA)，该算法基于模拟海豚对沙丁鱼群的探测、追逐和捕食机制进行优化。为了测试DSOA的性能，根据现有三种知名的SI优化算法(即粒子群优化算法(PSO)、蝙蝠算法(BA)和人工蜂群算法(ABC)的相应结果，对DSOA进行了评估，以找到一系列流行基准函数的全局最优能力。实验结果表明，该算法优于其他三种算法，具有收敛速度快、局部最优避免率高的特点。

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A New Stochastic Optimization Approach: Dolphin Swarm Optimization Algorithm

A novel nature-inspired swarm intelligence (SI) optimization is proposed called dolphin swarm optimization algorithm (DSOA), which is based on mimicking the mechanism of dolphins in detecting, chasing after, and preying on swarms of sardines to perform optimization. In order to test the performance, the DSOA is evaluated against the corresponding results of three existing well-known SI optimization algorithms, namely, particle swarm optimization (PSO), bat algorithm (BA), and artificial bee colony (ABC), in the terms of the ability to find the global optimum of a range of the popular benchmark functions. The experimental results show that the proposed optimization seems superior to the other three algorithms, and the proposed algorithm has the performance of fast convergence rate, and high local optimal avoidance.

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来源期刊

International Journal of Computational Intelligence and Applications COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-

CiteScore

2.90

自引率

0.00%

发文量

期刊介绍： The International Journal of Computational Intelligence and Applications, IJCIA, is a refereed journal dedicated to the theory and applications of computational intelligence (artificial neural networks, fuzzy systems, evolutionary computation and hybrid systems). The main goal of this journal is to provide the scientific community and industry with a vehicle whereby ideas using two or more conventional and computational intelligence based techniques could be discussed. The IJCIA welcomes original works in areas such as neural networks, fuzzy logic, evolutionary computation, pattern recognition, hybrid intelligent systems, symbolic machine learning, statistical models, image/audio/video compression and retrieval.