A cloud-based artificial immune network for optimization
作者： Zhonghua Li , Jianming Li , Dongliang Guo , Zhi Yang
DOI: 10.1109/ICNC.2013.6818052
关键词: Immune system 、 Mathematical optimization 、 Cloud computing 、 Algorithm 、 Cloning (programming) 、 Computer science 、 Optimization problem 、 Similarity (geometry) 、 Antibody 、 Series (mathematics) 、 Artificial immune system
摘要: This paper proposes an artificial immune network based on the cloud model (AINet-CM) for complex optimization problems. By introducing to evaluate candidate antibodies, three major operators are redesigned enhance convergence performance of AINet-CM. These increasing half cloud-based cloning operator, asymmetrical mutation operator and normal similarity suppression, respectively. Also, a dynamic searching step length is considered. A series numerical simulations arranged technical investigations systems (i.e., opt-aiNet, IA-AIS AAIS-2S) selected comparison with The experimental results suggest that proposed AINet-CM algorithm outperforms other algorithms in speed solution accuracy.
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