[1]轩　华,李坤博,曹　颖.带强制工期约束的混合柔性流水线调度[J].郑州大学学报(工学版),2026,47(01):49-57.[doi:10.13705/j.issn.1671-6833.2025.04.018]
　XUAN Hua,LI Kunbo,CAO Ying.Hybrid Flexible Flowline Scheduling with Deadline Constraints[J].Journal of Zhengzhou University (Engineering Science),2026,47(01):49-57.[doi:10.13705/j.issn.1671-6833.2025.04.018]
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带强制工期约束的混合柔性流水线调度()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
47
期数:
2026年01期
页码:
49-57
栏目:
出版日期:
2026-01-06

文章信息/Info

Title:
Hybrid Flexible Flowline Scheduling with Deadline Constraints
文章编号:
1671-6833(2026)01-0049-09
作者:
轩　华1;  李坤博1;  曹　颖2
1.郑州大学 管理学院,河南 郑州 450001;2.河南科技大学 土木建筑学院,河南 洛阳 471000
Author(s):
XUAN Hua1;  LI Kunbo1;  CAO Ying2
1.School of Management, Zhengzhou University, Zhengzhou 450001, China; 2.School of Civil Engineering and Architecture,Henan University of Science and Technology, Luoyang 471000, China
关键词:
混合柔性流水线;  强制工期;  ABC-WOA混合算法;  NEH启发式法
Keywords:
hybrid flexible flowline;  deadlines;  ABC-WOA hybrid algorithm;  NEH heuristic approach
分类号:
TB49N945
DOI:
10.13705/j.issn.1671-6833.2025.04.018
文献标志码:
A
摘要:
针对每阶段包含不相关并行机的混合柔性流水线问题,考虑强制工期和运输时间,以最小化总加权完成时间为目标建立整数规划模型,结合改进遗传算法和邻域搜索策略,提出一种人工蜂群算法和鲸鱼优化算法的混合算法以获取近优解。算法采用基于工件号编码以及NEH启发式法生成初始工件序列集,雇佣蜂阶段引入改进遗传算法产生更优质的工件序列,跟随蜂阶段利用5种邻域搜索策略以得到更好的邻域序列,在侦察蜂阶段设计基于最差解的鲸鱼优化算法提高算法搜索能力。仿真实验测试了混合人工蜂群和鲸鱼优化算法内改进项的有效性以及不同规模的算例。实验结果表明:所提出的混合算法具有较好的求解性能。
Abstract:
For the hybrid flexible flowline problem with unrelated parallel machines at each stage, with constraints on deadline and transportation time, an integer programming model was established to minimize the total weighted completion time. A hybrid algorithm of artificial bee colony algorithm and whale optimization algorithm (ABCWOA) was proposed by combining improved genetic algorithm and neighborhood search strategy to obtain near optimal solutions. The algorithm utilized encoding based on job numbers and the NEH heuristic method to generate an initial set of job sequences. In the employed bee phase, an improved genetic algorithm was introduced to produce higher-quality job sequences. In the onlooker bee phase, five neighborhood search strategies were utilized to obtain better neighboring sequences. In the scout bee phase, a whale optimization algorithm based on the worst solution was designed to enhance the search capabilities of the algorithm. Simulation experiments were conducted to test the effectiveness of the improvements within the hybrid ABC-WOA algorithm, as well as to examine instances of varying sizes. The experimental results showed that the proposed hybrid algorithm performed very well.

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更新日期/Last Update: 2026-01-17