%0 Journal Article
%T Solving multi-objective hybrid flow-shop scheduling problem based on genetic algorithm<br>基于遗传算法的混合流水线车间调度多目标求解*
%A YAO Li-li
%A SHI Hai-bo
%A LIU Chang
%A HAN Zhong-hu
%A <br>姚丽丽
%A 史海波
%A 刘昶
%A 韩忠华
%J 计算机应用研究
%D 2011
%I 
%X In order to solve the problem that the traditional multi-objective optimization algorithm is difficult to realize the practical decision of the enterprise, brought a novel multi-objective genetic algorithm forward to solve the hybrid flow-shop scheduling problems. According to the demand of the enterprise, based on sub-module using two modeling ideas, objectives were fallen into two categories: constrained objective and optimized objective, and the different objective had the different searching process. Finally, it used the novel algorithm to solve the multi-objective hybrid flow-shop scheduling problem. The result shows that the novel algorithm has the good feasibility, and it also has an obvious advantage, the better practicability and maneuverability, compared with the traditional multi-objective optimization methods.
%K genetic algorithm(GA)
%K hybrid flow-shop scheduling problem(HFSP)
%K multi-object optimization
%K constrained objective
%K optimized objective<br>遗传算法
%K 混合流水线车间调度
%K 多目标优化
%K 约束性目标
%K 优化性目标
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=49438F68A18A45248B1EA310BBD04936&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=9CF7A0430CBB2DFD&sid=FF1E6F72756FD105&eid=A1374D6ABE9C0DC0&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=13