%0 Journal Article
%T Improved adaptive genetic algorithm for expert assignment problem<br>一种改进的自适应遗传算法求解专家分配问题
%A LI Na-na
%A GU Jun-hua
%A SONG Jie
%A LIU Bo-ying
%A REN Chao
%A <br>李娜娜
%A 顾军华
%A 宋洁
%A 刘伯颖
%A 任超
%J 计算机应用
%D 2007
%I 
%X Expert assignment is chief and basic work of project review in project management. So it is significant to research how to solve expert assignment problem (EAP). In previous papers, we established the mathematical model of expert assignment problem, and proposed genetic algorithm and GA using heuristic mutation guide by pheromone to solve EAP. Though it has been proven they are effective ways for EAP, they have disadvantages of massive redundancy iteration in later period and inferior local search ability. In this paper a modification of GA which introduces adaptive mutation is proposed to solve EAP. The simulation results show that the new algorithm improves the ability of local search and generates solutions of better quality.
%K expert assignment
%K genetic algorithm
%K ant algorithm
%K adaptive mutation
%K pheromone<br>专家分配
%K 遗传算法
%K 蚂蚁算法
%K 自适应变异
%K 信息素
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=831E194C147C78FAAFCC50BC7ADD1732&aid=863C78CF5AD0A097A10753B17909A7CD&yid=A732AF04DDA03BB3&vid=DB817633AA4F79B9&iid=9CF7A0430CBB2DFD&sid=E5322D16BA846136&eid=1C97F4100B4B07F1&journal_id=1001-9081&journal_name=计算机应用&referenced_num=0&reference_num=10