文献类型：期刊文献

英文题名：On improved parallel immune quantum evolutionary algorithm based on learning mechanism and its performance

作者：You, Xiaoming[1,2]; Shuai, Dianxun[2]; Liu, Sheng[1,2]

机构：[1] College of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 200065, China; [2] Dept of Computer Science and Technology, East China University of Science and Technology, Shanghai 200237, China

年份：2006

卷号：3

期号：4

起止页码：1005

外文期刊名：Journal of Information and Computational Science

收录：EI(收录号：20071610557036)

语种：英文

外文关键词：Convergence of numerical methods - Learning algorithms - Parallel algorithms

摘要：A modified Multi-universe Parallel Immune Quantum Evolutionary Algorithm based on Learning Mechanism (MPMQEA) is proposed, in the algorithm, all individuals are divided into some independent sub-colonies, called universes. Their topological structure is analyzed and modified; information among the universes is exchanged by adopting emigration based on improving learning mechanism and adaptive quantum interaction simulating entanglement of quantum. It not only can maintain quite nicely the population diversity, but also can help to converge to the global optimal solution rapidly. We describe technique for improving the performance of MPMQEA and its superiority is shown by some simulation experiments.