%0 Journal Article
%T Advances in quantum genetic algorithm<br>量子遗传算法研究进展
%A LIANG Chang-yong
%A BAI Hua
%A CAI Mei-ju
%A LU Wen-xing
%A <br>梁昌勇
%A 柏　桦
%A 蔡美菊
%A 陆文星
%J 计算机应用研究
%D 2012
%I 
%X This paper firstly introduced the origin of the quantum genetic algorithm QGA, basic theories and methods. Secondly, it discussed the improved methods QGA from four perspectives which are improvement of quantum gates, adding new operators, the parallelism of QGA and hybrid QGA, then summarized the applications of QGA. Finally, it proposed the future directions.
%K quantum gate
%K quantum computing
%K qubit
%K quantum genetic algorithm(QGA)<br>量子门
%K 量子计算
%K 量子比特
%K 量子遗传算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=3178011684088478750AA6F8220A785A&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=DF92D298D3FF1E6E&sid=C60F9D75D8506098&eid=AAC7B2D4995BA8E4&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=45