DocumentCode
476016
Title
Hybrid genetic-VNS algorithm with total flowtime minimization for the no-wait flowshop problem
Author
Yang, Ning ; Li, Xiao-ping ; Zhu, Jie ; Wang, Qian
Author_Institution
Sch. of Comput. Sci. & Eng., Southeast Univ., Nanjing
Volume
2
fYear
2008
fDate
12-15 July 2008
Firstpage
935
Lastpage
940
Abstract
In this paper, a hybrid genetic-VNS algorithm is proposed for the no-wait flowshop problem with total flowtime minimization. To avoid pitfalls of GA, such as poor local search capability and premature convergence, a rather effective VNS local search is introduced based on the framework of the improved GA. To fast convergence of the algorithm, ICH2 (an efficient composite heuristic) is used for the initial population generation. Experimental results show that the proposed algorithm outperforms other best two recent existing methods on both small and large instances.
Keywords
flow shop scheduling; genetic algorithms; minimisation; composite heuristic; hybrid genetic-VNS algorithm; initial population generation; no-wait flowshop problem; scheduling problem; total flowtime minimization; Computer science; Convergence; Cybernetics; Genetic mutations; Job shop scheduling; Machine learning; Machine learning algorithms; Minimization methods; Stochastic processes; Thin film transistors; Hybrid Genetic-VNS algorithm; no-wait flowshop; scheduling; total flowtime;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4620539
Filename
4620539
Link To Document