摘要
针对不确定环境下移动式装配的项目存在项目工期随机延长的问题,首先引用项目拆分思想,将单项目虚拟拆分成多项目;在加入最大鲁棒性约束下,以最小化项目工期为目标建立数学优化模型。提出了改进的两阶段循环算法求解:项目划分阶段通过子项目拆分算法进行子项目划分;项目调度阶段以布谷鸟算法为框架对划分后的多项目调度进行求解,并将调度结果反馈至上阶段。最后选取PSPLIB算例库中不同规模的算例,分析各种参数在不同规模下对项目计划的影响。实例验证结果表明,所提方法能在不确定环境下提高项目资源利用率并缩短工期。
In the view of the problem of project makespan extended randomly which background with specific product moving assembly line under uncertain environment.Firstly,the paper broke an original project into multiple projects virtually by using the idea of project splitting.And it established an optimization mathematical model to make the objective function of minimizing project makespan on the basis of considering the maximum robustness constraints.This paper developed a two-level iterative algorithm.At the project splitting level,it adjusted jobs between projects by a job allocation heuristic algorithm.At the project scheduling level,it applied a self-adaption cuckoo algorithm scheme to generate feasible schedules and returned the result to the last level for iteration.To analyze project outcome,it changed selecting examples of different scales in PSPLIB.The results show that the proposed algorithm can improve the utilization rate of project resources and shorten the activity durations under uncertain environment.
作者
欧阳凌霞
倪静
Ouyang Lingxia;Ni Jing(School of Business,University of Shanghai for Science&Technology,Shanghai 200093,China)
出处
《计算机应用研究》
CSCD
北大核心
2020年第10期3025-3029,共5页
Application Research of Computers
基金
国家教育部人文社会科学基金资助项目(19YJAZH064)。
关键词
多项目
任务网络
时间不确定
项目调度
自适应布谷鸟算法
multiple projects
task network
time uncertainty
project scheduling
adaptive cuckoo algorithm
