基于混合变邻域遗传算法的电堆装配线优化
Simulation and Optimization of the Stack Assembly Line Employing a Hybrid Variable Neighborhood Genetic Algorithm
李佳萍 1孙斌 2钟华庚 2杜宇 3刘冬2
作者信息
- 1. 大连豪森设备制造股份有限公司,大连 116036
- 2. 大连理工大学机械工程学院,大连 116024
- 3. 大连交通大学机械工程学院,大连 116028
- 折叠
摘要
传统的电堆装配线生产线效率低,为提高电堆装配生产线效率,对装配线进行优化.首先,建立了以最小化工作站数量和工人数量的数学模型,提出了在自动化装配线的条件下允许工作站共用工人的分配方法;其次,针对平行装配线平衡问题提出了一种混合变邻域搜索遗传算法(HVGA)求解大规模问题;然后,对燃料电池电堆装配线例子进行了仿真验证与分析,提出了仿真目标,建立了平衡优化前后的仿真模型;最后,对仿真模型进行对比分析.平衡后工作站的平均利用率从75.52%提高到了82.53%,提高了7.01%,同时工人的平均利用率从52.1%提高到了73.2%,提高了21.1%,与平衡结果基本一致,验证了平行装配线平衡方法与工人分配方法的有效性.
Abstract
In order to improve the efficiency of the traditional assembly line,the assembly line is opti-mized.First,a mathematical model to minimize the number of workstations and the number of workers is developed,and an allocation method that allows workstations to share workers under the conditions of an automated assembly line is proposed.Secondly,a hybrid variable neighborhood search genetic algorithm(HVGA)is proposed to solve the large-scale problem for the parallel assembly line balancing problem.Af-terwards,the fuel cell stack assembly line example is simulated to verify and analyze the simulation objec-tives.The simulation model before and after balancing optimization is established,and finally the simulation model is compared and analyzed,and the average utilization rate of the workstation after balancing is in-creased from 75.52%to 82.53%,which is an increase of 7.01%.Meanwhile the average utilization rate of workers increased from 52.1%to 73.2%,an increase of 21.1%,which is basically consistent with the balancing results,verifying the effectiveness of the balancing method of parallel assembly line and the worker allocation method.
关键词
flexsim/装配任务类型/工人分配/电堆装配线/遗传算法/装配线优化Key words
flexsim/type of assembly task/worker assignment/electric stack assembly line/genetic algo-rithm/assembly line optimization引用本文复制引用
基金项目
辽宁省揭榜挂帅科技攻关项目(2021JH1/10400062)
大连市揭榜挂帅科技攻关项目(2021JB12GX031)
出版年
2024
NETL
NSTL
万方数据