A hybrid social emotional optimization algorithm with Metropolis rule

Jianna Wu, Z. Cui, Jing Liu
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引用次数: 5

Abstract

Social emotional optimization algorithm (SEOA) is a novel swarm intelligent population-based optimization algorithm by simulating the human social behaviors. However, it's diversity is decreased increased when solving high-dimensional multi-modal optimization problems. Therefore, in this paper, a new hybrid SEOA with Metropolis rule is introduced to enhance the exploration capability. To test the performance, five famous benchmarks are selected, and compared with the standard version with different dimensions. Simulation results show this hybrid algorithm can increase the global search capability significantly.
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基于Metropolis规则的混合型社会情感优化算法
社会情感优化算法(SEOA)是一种模拟人类社会行为的基于群体智能群体的优化算法。然而,在求解高维多模态优化问题时,算法的多样性有所下降。为此,本文提出了一种新的基于Metropolis规则的混合型SEOA,以增强其搜索能力。为了测试性能,选择了五个著名的基准测试,并与不同维度的标准版本进行了比较。仿真结果表明,该混合算法能显著提高全局搜索能力。
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