文献类型：期刊文献

英文题名：An asynchronous genetic local search algorithm for the permutation flowshop scheduling problem with total flowtime minimization

作者：Xu, Xiao[1];Xu, Zhenhao[1];Gu, Xingsheng[1]

机构：[1]E China Univ Sci & Technol, Sch Informat, Shanghai 200237, Peoples R China

年份：2011

卷号：38

期号：7

起止页码：7970

外文期刊名：EXPERT SYSTEMS WITH APPLICATIONS

收录：;EI(收录号：20111113737817);WOS:【SCI-EXPANDED(收录号:WOS:000289047700008)】；

基金：This work is funded by the National Natural Science Foundation of China (No. 60774078), the National High Technology Research and Development Program of China (No. 2009AA04Z141), Shanghai Municipal Natural Science Foundation (No. 10ZR1408300) and the Fundamental Research Funds for the Central Universities. The authors would also like to thank Dr. Ruben Ruiz for his constructive comments and contribution to the completion of the work.

语种：英文

外文关键词：Scheduling; Genetic algorithm; Permutation flow shop; Total flowtime

摘要：In this study, the permutation flowshop scheduling problem with the total flowtime criterion is considered. An asynchronous genetic local search algorithm (AGA) is proposed to deal with this problem. The AGA consists of three phases. In the first phase, an individual in the initial population is yielded by an effective constructive heuristic and the others are randomly generated, while in the second phase all pairs of individuals perform the asynchronous evolution (AE) where an enhanced variable neighborhood search (E-VNS) as well as a simple crossover operator is used. A restart mechanism is applied in the last phase. Our experimental results show that the algorithm proposed outperforms several state-of-the-art methods and two recently proposed meta-heuristics in both solution quality and computation time. Moreover, for 120 benchmark instances, AGA obtains 118 best solutions reported in the literature and 83 of which are newly improved. (C) 2011 Published by Elsevier Ltd.