摘要
针对NP-难的最小化时间表长为目标的无等待流水车间调度问题,将此问题转化为旅行商问题。采用蚁群优化求得初始工件排序。在提出的一种新的邻域结构基础上,迭代进行集中和分散的变邻域搜索以改善解。用Rec系列及hel1和hel2共计23个Benchmark算例进行计算验证,并与RAJ算法进行了比较。结果表明所提出的方法是有效的。
To solve NP-hard no-wait flow shop scheduling problem with the makespan minimization criterion,this question is first turned into a Traveling Salesman Problem（TSP）.Then Ant Colony Optimization（ACO）is used to construct an initial job sequence.Based on a new proposed neighborhood,intensification and diversification variable neighborhood search is interchangeably evolved to improve solution.The performance of the algorithm is tested on Rec,hel1 and hel2 Benchmark problems.The results are compared to the well-known RAJ heuristic.The computational results indicate the effectiveness of the proposed approach.
出处
《计算机工程与应用》
CSCD
2012年第16期216-219,248,共5页
Computer Engineering and Applications
关键词
流水车间
无等待
时间表长
蚁群优化
变邻域搜索
flowshop
no-wait
makespan
ant colony optimization
variable neighborhood search
