A discrete gravitational search algorithm for the blocking flow shop problem with total flow time minimization
A discrete gravitational search algorithm for the blocking flow shop problem with total flow time minimization
复制标题
总流程时间最小化阻塞流水车间问题的离散引力搜索算法
DOI：
10.1007/s10489-019-01457-w
复制
发表时间：
2019-04
影响因子：
5.3
通讯作者：
Song Houbin
中科院分区：
文献类型：
--
作者：
Zhao Fuqing;Xue Feilong;Zhang Yi;Ma Weimin;Zhang Chuck;Song Houbin
阻塞流水车间问题是制造系统流水车间调度问题的关键模型之一。引力搜索算法（GSA）是一种基于种群的求解各种优化问题的算法。然而，GSA很少被应用于解决BFSP，因为它被设计用于解决连续问题。本文提出了一种求解总流动时间最小的BFSP问题的离散引力搜索算法（DGSA）。为了平衡初始种群的质量和多样性，提出了一种新的可变轮廓拟合算法VPF_NEH（n）。在候选节点的位置更新过程中实现了可变邻域算子、路径重连算子和加算子。该操作的目的是防止种群的早熟收敛，并在优化过程中平衡探索和开发。通过基于层次的理论分析了DGSA的期望运行时间。仿真结果表明了DGSA算法的有效性和优越性。
The blocking flow shop problem (BFSP) is one of the key models in the flow shop scheduling problem in the manufacturing systems. Gravitational Search Algorithm (GSA) is an algorithm based on the population for solving various optimization problems. However, GSA is scarcely applied to solve the BFSP as it is designed to solve the continuous problems. In this paper, a Discrete Gravitational Search Algorithm (DGSA) is presented for solving the BFSP with the total flow time minimization. A new variable profile fitting (VPF) combined with NEH heuristic, namedVPF_NEH(n), is introduced for balancing the quality and the diversity of the initial population to configure the DGSA. The three operators including the variable neighborhood operators (VNO), the path relinking and the plus operator are implemented during the location updating of the candidates. The objective of the operation is to prevent the premature convergence of the population and to balance the exploration and exploitation in the process of optimization. The expected runtime of the DGSA is analyzed by the level-based theorem. The simulated results indicate that the effectiveness and superiority of the DGSA.
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DOI：
10.1016/0305-0483(83)90088-9
发表时间：
1983-01-01
影响因子：
6.9
作者：
NAWAZ, M;ENSCORE, EE;HAM, I
通讯作者：
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影响因子：
1.6
作者：
V. Yazdanpanah;D. Yazan;W. Zijm
通讯作者：
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DOI：
10.1007/978-1-4613-0303-9
发表时间：
1998-10
期刊：
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影响因子：
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作者：
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通讯作者：
D. Du;P. Pardalos
DOI：
10.1145/2598394.2605342
发表时间：
2014-07
期刊：
Proceedings of the Companion Publication of the 2014 Annual Conference on Genetic and Evolutionary Computation
影响因子：
--
作者：
A. Engelbrecht
通讯作者：
A. Engelbrecht
DOI：
10.1016/j.eswa.2017.01.006
发表时间：
2017-05
期刊：
Expert Syst. Appl.
影响因子：
--
作者：
Imma Ribas;R. Companys;X. Tort-Martorell
通讯作者：
Imma Ribas;R. Companys;X. Tort-Martorell