Evolutionary multi-objective blocking lot-streaming flow shop scheduling with interval processing time

Evolutionary multi-objective blocking lot-streaming flow shop scheduling with interval processing time
复制标题

具有间隔处理时间的进化多目标分块批量流水车间调度

DOI:
10.1016/j.asoc.2016.01.033
复制
发表时间:
2016-05
影响因子:
8.7
通讯作者:
Pan Q. K
Pan Q. K
中科院分区:
计算机科学2区
文献类型:
--
作者:
Han Y.;Gong D;Jin Y;Pan Q. K

文献摘要

参考文献

被引文献

相似文献

具有间歇处理时间的阻塞批流车间调度问题在各种工业系统中有着广泛的应用,但目前尚未得到很好的研究。本文将该问题表述为一个多目标优化问题,其中每个区间目标通过其中点和半径的动态加权和转化为一个实值目标。针对重新表述的多目标优化问题,提出了一种新的进化多目标优化算法,该算法在设计交叉算子时利用了非支配解和父类之间的差异,并采用理想点辅助局部搜索策略进行多目标优化,提高了算法的挖掘能力。为了对该算法的性能进行实证评价,在24个调度实例上进行了一系列对比实验。实验结果表明,该算法在收敛性上优于同类算法,具有较强的不确定性处理能力。
A blocking lot-streaming flow shop scheduling problem with interval processing time has a wide range of applications in various industrial systems, however, not yet been well studied. In this paper, the problem is formulated as a multi-objective optimization problem, where each interval objective is converted into a real-valued one using a dynamically weighted sum of its midpoint and radius. A novel evolutionary multi-objective optimization algorithm is then proposed to solve the re-formulated multi-objective optimization problem, in which non-dominated solutions and differences among parents are taken advantage of when designing the crossover operator, and an ideal-point assisted local search strategy for multi-objective optimization is employed to improve the exploitation capability of the algorithm. To empirically evaluate the performance of the proposed algorithm, a series of comparative experiments are conducted on 24 scheduling instances. The experimental results show that the proposed algorithm outperforms the compared algorithms in convergence, and is more capable of tackling uncertainties.
DOI: 10.1016/j.cor.2014.06.003
发表时间: 2014-11
期刊: Comput. Oper. Res.
影响因子: --
作者:
A. Allahverdi;H. Aydilek;Asiye Aydilek
通讯作者: A. Allahverdi;H. Aydilek;Asiye Aydilek
DOI: 10.1016/j.eswa.2011.09.050
发表时间: 2012-02
期刊: Expert Syst. Appl.
影响因子: --
作者:
S. Horng;Shieh-Shing Lin;Feng-Yi Yang
通讯作者: S. Horng;Shieh-Shing Lin;Feng-Yi Yang
DOI: 10.1007/s00500-014-1219-7
发表时间: 2014-01
期刊: Soft Computing
影响因子: 4.1
作者:
D. Davendra;R. Šenkeřík;I. Zelinka;Michal Pluhacek;M. Bialic-Davendra
通讯作者: D. Davendra;R. Šenkeřík;I. Zelinka;Michal Pluhacek;M. Bialic-Davendra
DOI: 10.1016/j.ejor.2011.08.029
发表时间: 2012-02
期刊: Eur. J. Oper. Res.
影响因子: --
作者:
A. Kasperski;Adam Kurpisz;P. Zieliński
通讯作者: A. Kasperski;Adam Kurpisz;P. Zieliński
DOI: 10.1016/j.ejor.2007.08.030
发表时间: 2008-12
期刊: Eur. J. Oper. Res.
影响因子: --
作者:
C. Tseng;C. Liao
通讯作者: C. Tseng;C. Liao