首页 | 本学科首页   官方微博 | 高级检索  
     

大型工程项目任务多目标优化调度方法
引用本文:曾强,杨育,王小磊,赵川.大型工程项目任务多目标优化调度方法[J].计算机工程与应用,2010,46(24):217-221.
作者姓名:曾强  杨育  王小磊  赵川
作者单位:1.重庆大学 机械传动国家重点实验室,重庆 400030 2.河南理工大学,河南 焦作 454000
基金项目:国家自然科学基金,国家教育部"新世纪优秀人才支持计划" 
摘    要:提出了一种大型工程项目任务多目标优化调度方法。构建了一种以项目工期最小化、费用最小化及质量最大化为目标函数的多目标优化模型;针对模型的多变量、多约束、大组合量特点,提出了一种基于自适应变异和模拟退火思想的改进蚁群算法。将模型和算法在某大型工程项目任务调度中加以应用,验证了所提出的优化调度方法的正确性和有效性。

关 键 词:任务调度  多目标决策  蚁群算法  自适应变异  模拟退火算法
收稿时间:2009-12-8
修稿时间:2010-2-8  

Multi-objective optimization method for tasks scheduling of large-scale engineering project
ZENG Qiang,YANG Yu,WANG Xiao-lei,ZHAO Chuan.Multi-objective optimization method for tasks scheduling of large-scale engineering project[J].Computer Engineering and Applications,2010,46(24):217-221.
Authors:ZENG Qiang  YANG Yu  WANG Xiao-lei  ZHAO Chuan
Affiliation:1.State Key Laboratory of Mechanical Transmissions,Chongqing University,Chongqing 400030,China 2.Henan Polytechnic University,Jiaozuo,Henan 454000,China
Abstract:A multi-objective optimization method for tasks scheduling of large-scale engineering project is proposed.In the method,a multi-objective programming model is established with the objective to minimize the completion time and total expenses and to maximize the total quality of the project.Considering the model's characteristic of multi-vary,multi-restriction and large solution space,a hybrid algorithm named improved ant colony algorithm based on adaptive mutation probability and simulated annealing thought is proposed.The application in a large-scale engineering project tasks assignment example validates the correctness and effectiveness of the method.
Keywords:tasks scheduling  multi-objective decision  ant colony algorithm  adaptive mutation probability  simulated annealing algorithm
本文献已被 维普 万方数据 等数据库收录!
点击此处可从《计算机工程与应用》浏览原始摘要信息
点击此处可从《计算机工程与应用》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号