文献类型：期刊文献

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

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

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

年份：2006

卷号：4221 LNCS - I

起止页码：903

外文期刊名：Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

收录：EI(收录号：20064410206695)

语种：英文

外文关键词：Computer simulation - Convergence of numerical methods - Learning algorithms - Learning systems - Quantum theory

摘要：A novel 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 defined, each universe evolving independently uses the immune quantum evolutionary algorithm, and information among the universes is exchanged by adopting emigration based on the learning mechanism and quantum interaction simulating entanglement of quantum. It not only can maintain quite nicely the population diversity, but also can help to accelerate the convergence speed and converge to the global optimal solution rapidly. The convergence of the MPMQEA is proved and its superiority is shown by some simulation experiments in this paper. ? Springer-Verlag Berlin Heidelberg 2006.