[1]朱　斌,马　骁,李稷丰,等.钢桥板单元分布式柔性作业车间成组调度[J].郑州大学学报(工学版),2026,47(01):41-48.[doi:10.13705/j.issn.1671-6833.2026.01.002]
　ZHU Bin,MA Xiao,LI Jifeng,et al.Distributed Flexible Job-shop Group Scheduling for Steel Bridge Plate Units[J].Journal of Zhengzhou University (Engineering Science),2026,47(01):41-48.[doi:10.13705/j.issn.1671-6833.2026.01.002]
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钢桥板单元分布式柔性作业车间成组调度()
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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:
41-48
栏目:
出版日期:
2026-01-06

文章信息/Info

Title:
Distributed Flexible Job-shop Group Scheduling for Steel Bridge Plate Units
文章编号:
1671-6833(2026)01-0041-08
作者:
朱　斌1;  马　骁1;  李稷丰1;  雷景媛1; 2
1.长安大学 陕西省高速公路施工机械重点实验室,陕西 西安 710064;2.西安石油大学 机械工程学院,陕西 西安 710065
Author(s):
ZHU Bin1;  MA Xiao1;  LI Jifeng1;  LEI Jingyuan1; 2
1.Key Laboratory of Expressway Construction Machinery of Shaanxi Province, Chang’an University, Xi’an 710064, China; 2.Mechanical Engineering College, Xi’an Shiyou University, Xi’an 710065, China
关键词:
钢桥板单元;  柔性作业车间;  成组调度;  顺序相关;  运输时间;  混合遗传禁忌搜索算法
Keywords:
steel bridge plate unit;  flexible job-shop;  group scheduling;  sequence-dependent;  transportation time;  hybrid genetic tabu search algorithm
分类号:
TH181U445.8
DOI:
10.13705/j.issn.1671-6833.2026.01.002
文献标志码:
A
摘要:
针对钢桥板单元生产速度过慢会直接制约桥梁工程建设周期的问题,在考虑钢桥板单元的加工工艺路线和生产特点的同时,以最小化最大完工时间为目标,建立了考虑顺序相关作业切换时间和运输时间,面向钢桥板单元加工的分布式柔性作业车间成组调度(DFJGSPST)模型,并提出了基于三层编码的记忆混合遗传禁忌搜索算法(MGATS)。为验证数学模型和智能算法的可行性,以某钢桥板单元生产为例,建立了包括4种板单元组和15台机器的DFJGSPST模型,通过相应的测试算例进行实验验证,并与其他智能算法进行比较分析。实验结果表明:所提的MGATS的相对百分比差异(RPD)的均值为2.74%,低于遗传算法(GA)的3.99%和混合遗传禁忌搜索算法(GATS)的3.13%。MGATS的成功率(SR)为0.15,高于GATS和GA,验证了MGATS在求解DFJGSPST模型中的稳定性和鲁棒性。
Abstract:
To address the issue of slow production speed of steel bridge plate units, which directly constrained the construction period of bridge engineering projects, a distributed flexible job-shop group scheduling problem with setup & transportation time (DFJGSPST) model for steel bridge plate unit processing was established to minimize the maximum completion time while considering the processing technology route and production characteristics. A memory-based genetic algorithm with tabu search (MGATS) based on a three-layer encoding strategy was proposed to solve the model. To verify the feasibility of the mathematical model and intelligent algorithm, a DFJGSPST model comprising four types of plate unit groups and fifteen machines was established using a real-world steel bridge plate unit production case. Relevant test instances were selected for experimental validation and comparative analysis with other intelligent algorithms. Experimental results showed that the proposed MGATS algorithm achieved a mean relative percentage difference (RPD) of 2.74%, which was lower than that of the genetic algorithm (GA) at 3.99%, and hybrid genetic tabu search algorithm (GATS) at 3.13%. The success rate (SR) of the MGATS algorithm was 0.15, which was higher than that of the GATS algorithm and the GA algorithm, which verified the stability and robustness of the MGATS algorithm in solving the DFJGSPST model.

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更新日期/Last Update: 2026-01-17