%0 Journal Article
%T Quantum Probability Coding Genetic Algorithm and Its Applications<br>量子概率编码遗传算法及其应用
%A Li Bin
%A Tan Li-xiang
%A Zou Yi
%A Zhuang Zhen-quan
%A <br>李斌
%A 谭立湘
%A 邹谊
%A 庄镇泉
%J 电子与信息学报
%D 2005
%I 
%X A Quantum probability Coding Genetic Algorithm-QCGA is proposed, which is different from classical GAs. In QCGA, single individual represents a probability distribution of solutions, which covers the whole solution space. Individuals in QCGA evolve independently and in parallel. A new crossover operator is designed to implement the information exchange among individuals. A new mutation operator is also design to prevent the algorithm from falling into local optima. To study the efficiency and advantage of QCGA, the algorithm is applied to solve function optimization problems, knapsack problems, and to discover frequent structures from time series. Experimental results show that QCGA has good ability of global optimization, and good ability of diversity reservation, which makes it efficient for complex optimization problems.
%K Genetic algorithm
%K Quantum probability coding
%K Crossover operator
%K Mutation operator<br>遗传算法
%K 量子概率编码
%K 交叉算子
%K 变异算子
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=1319827C0C74AAE8D654BEA21B7F54D3&jid=EFC0377B03BD8D0EF4BBB548AC5F739A&aid=511C70C04C660450&yid=2DD7160C83D0ACED&vid=DB817633AA4F79B9&iid=94C357A881DFC066&sid=8C8D39B86A1EED4F&eid=4A2C67480A6B9F95&journal_id=1009-5896&journal_name=电子与信息学报&referenced_num=8&reference_num=10