基于改进NSGA-Ⅱ算法的多阶段混合流水装配车间工人分配方法

doi:10.3901/JME.2025.15.417

机械工程学报 ›› 2025, Vol. 61 ›› Issue (15): 417-440.doi: 10.3901/JME.2025.15.417

• 人机协作装配与调度 • 上一篇

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基于改进NSGA-Ⅱ算法的多阶段混合流水装配车间工人分配方法

杨震¹, 高丰¹, 刘检华^1,2, 孟昭旭³, 沙金龙³, 庄存波^1,2

1. 北京理工大学机械与车辆学院北京 100081;
2. 北京理工大学唐山研究院河北省智能装配与检测技术重点实验室唐山 063000;
3. 中国兵器工业第二〇八研究所北京 102202

收稿日期:2024-09-10 修回日期:2024-12-13 发布日期:2025-09-28
作者简介:杨震，男，2000年出生。主要研究方向为车间调度与数字孪生。E-mail：yangzhen_bit@qq.com;高丰，男，1984年出生。主要研究方向为先进制造技术。E-mail：swai1213@163.com;刘检华，男，1977年出生，博士，教授，博士研究生导师。主要研究方向为数字化装配技术。E-mail：jeffliu@bit.edu.cn;孟昭旭，男，1988年出生，学士，正高级工程师。主要研究方向为数字化制造。E-mail：475700100@qq.com;沙金龙，男，1968年出生，硕士，正高级高级工程师。主要研究方向为数字化设计与制造。E-mail：sjlong_208VIP@163.com;庄存波(通信作者)，男，1991年出生，博士，副研究员，硕士研究生导师。主要研究方向为装配MES、数字孪生车间。E-mail：zhuangdavid@bit.edu.cn
基金资助:
国防基础科研资助项目(JCKY2022209B001)。

Multi-stage Hybrid Flow Assembly Workshop Worker Assignment Method Based on Improved NSGA-Ⅱ Algorithm

YANG Zhen¹, GAO Feng¹, LIU Jianhua^1,2, MENG Zhaoxu³, SHA Jinlong³, ZHUANG Cunbo^1,2

1. School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081;
2. Hebei Key Laboratory of Intelligent assembly and Detection technology, Tangshan Research Institute, Beijing Institute of Technology, Tangshan 063000;
3. No. 208 Research Institute of China Ordnance Industries, Beijing 102202

Received:2024-09-10 Revised:2024-12-13 Published:2025-09-28

摘要/Abstract

摘要： 当前手工装配车间工人分配多依赖管理者经验，易致排产效率低、工人忙闲不均。为此，研究考虑工人技能类型、技能水平、年龄大小等多人力因素的多阶段混合流水车间工人分配问题至关重要。针对该问题，建立以最小化订单完工时间和工人负载均衡为目标的调度优化模型，提出改进NSGA-Ⅱ算法。为实现不同阶段工人编码，设计一种多层染色体结构编码方法。考虑工人技能类型的影响，设计一种染色体交叉变异方法。为避免算法陷入局部最优解，设计一种基于变异方法的局部搜索策略。以某士兵装备生产车间为例，设计32个测试案例进行算法对比试验。结果表明该算法在稳定性、收敛性和解的质量方面优于其他六种算法。为解决多阶段混合流水车间工人分配问题提供了新方法。

关键词: 装配车间, 工人分配, 人力因素, 改进NSGA-Ⅱ算法

Abstract: In the current manual assembly workshops, worker assignment heavily relies on the experience of managers, often resulting in low scheduling efficiency and uneven workloads among workers. To address this issue, studying the multi-stage hybrid flow shop worker assignment problem, considering various human factors such as skill types, skill levels, and age, is crucial. For this problem, a scheduling optimization model is established with the objectives of minimizing order completion time and balancing worker loads. An improved NSGA-Ⅱ algorithm is proposed. A multi-layer chromosome structure coding method is developed to encode workers for different stages. A chromosome crossover and mutation method is introduced to account for the impact of worker skill types. To prevent the algorithm from falling into local optima, a local search strategy based on a mutation method is proposed. Taking a soldier equipment production workshop as an example, 32 test cases are designed for algorithm comparison experiments. The results demonstrate that the proposed algorithm outperforms six other algorithms in terms of stability, convergence, and solution quality. Providing a novel method for solving the multi-stage hybrid flow shop worker assignment problem.

Key words: assembly workshop, worker assignment, human factors, improved NSGA-Ⅱ algorithm

中图分类号:

TB497

杨震, 高丰, 刘检华, 孟昭旭, 沙金龙, 庄存波. 基于改进NSGA-Ⅱ算法的多阶段混合流水装配车间工人分配方法[J]. 机械工程学报, 2025, 61(15): 417-440.

YANG Zhen, GAO Feng, LIU Jianhua, MENG Zhaoxu, SHA Jinlong, ZHUANG Cunbo. Multi-stage Hybrid Flow Assembly Workshop Worker Assignment Method Based on Improved NSGA-Ⅱ Algorithm[J]. Journal of Mechanical Engineering, 2025, 61(15): 417-440.

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基于改进NSGA-Ⅱ算法的多阶段混合流水装配车间工人分配方法

Multi-stage Hybrid Flow Assembly Workshop Worker Assignment Method Based on Improved NSGA-Ⅱ Algorithm

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