%0 Journal Article
%T Hybrid particle swarm optimization algorithm based on differential evolution for project scheduling problems<br>多目标微粒群优化算法及其应用研究进展
%A lijinzhong
%A <br>李金忠
%A 夏洁武
%A 唐卫东
%A 曾劲涛
%A 刘新明
%A 王博
%J 计算机应用研究
%D 2011
%I 
%X Multi-objective particle swarm optimization (MOPSO) algorithm is a new global multi-objective optimization method based on swarm intelligence, which has been attracted much increasing interest and applied to various fields successfully. This paper aims at providing a review and discussion of MOPSO algorithm and its application in the recent years. Firstly, the basic framework of MOPSO algorithm is briefly described. Then, a taxonomy for MOPSO algorithms is proposed and analyzed, and some effective strategies are also presented, which can improve the performance of MOPSO algorithms. Thereafter, some typical applications of MOPSO algorithms are introduced. Finally, some promising directions for future research in this field are pointed out.
%K Multi-objective optimization
%K Multi-objective particle swarm optimization
%K Algorithm
%K Application<br>多目标优化
%K 多目标微粒群优化
%K 算法
%K 应用
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=B323C779AE12236EE9073A712C436A06&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=E158A972A605785F&sid=7D257F36093061DE&eid=328E221C70C13B92&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=89