A novel hybrid optimization algorithm combined with BBO and PSO
A novel hybrid optimization algorithm combined with BBO and PSO
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DOI：
10.1109/ccdc.2016.7531166
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发表时间：
2016-05
期刊：
影响因子：
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通讯作者：
Gang Cheng;Chao Lv;Shi Yan;Li Xu
中科院分区：
文献类型：
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作者：
Gang Cheng;Chao Lv;Shi Yan;Li Xu
将基于生物地理的优化算法(BBO)和粒子群优化算法(PSO)相结合，提出了一种新的混合优化算法BBO-PSO。在该优化算法中，采用BBO算法进行局部搜索，而采用PSO算法进行全局搜索，使算法在解空间具有强大的搜索能力。本文提出的算法和现有的3种优化算法在6个基准测试上进行了测试，仿真结果表明BBO-PSO算法具有较好的性能。
In this paper, a novel hybrid optimization algorithm named BBO-PSO is proposed, which is a combination of biogeography-based optimization (BBO) and particle swarm optimization (PSO). In this optimization algorithm, BBO will be employed for local search while PSO will be employed for global search, which makes the algorithm possess powerful search ability in the solution space. The proposed algorithm and 3 existing optimization algorithms are tested on 6 well known benchmarks and the simulation results show that BBO-PSO has better performance than the others.