%0 Journal Article
%T Based on genetic algorithm for Job Shop scheduling problem<br>基于遗传算法的Job Shop调度问题研究
%A JING Bo
%A LIU Ying
%A HUANG Bing
%A <br>景　波
%A 刘　莹
%A 黄　兵
%J 计算机应用研究
%D 2013
%I 
%X This study addressed a job scheduling and resource allocation problem with distinct release dates and due dates to minimize total tardiness in parallel work centers with a multi-processor environment. To solve the problem, this study also proposed a hybrid genetic algorithm (HGA) with release and due dates based decomposition heuristic. Experimental results show that the percentage deviations between the HGA and Lingo are smaller than 15%, and the HGA has smaller variance than the GA. This study proposed a decision-supporting model, which integrated simulation, genetic algorithms and decision support tools, for solving the JSRA problem by practical perspective.
%K 车间调度问题
%K 遗传算法
%K 资源分配
%K 总延迟时间
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=57319E4289F4438FB2160171E6CC7435&yid=FF7AA908D58E97FA&vid=340AC2BF8E7AB4FD&iid=38B194292C032A66&sid=2A22E972FD97071B&eid=09F7C8D609E885AE&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=12