摘要
大多数排产优化的研究往往针对一条生产线解决单一LBFFSP问题,无法针对企业缓冲区有限和多生产线等多因素的实际情况解决排产优化。针对该问题,提出了一种基本粒子群算法(Particle Swarm Optimization,PSO)作为全局优化算法。引用了基于惯性权重的粒子群算法,通过改进该算法有效地避免基本粒子群算法陷入局部最优。建立以最小化生产周期和最佳缓冲区容量为多目标的带有有限缓冲区的混流装配线排产优化数学模型。采用PSO算法进行生产排序的结果与传统方法的排序相比较,缩短生产周期6.7%。提出的排序方案可以显著提高企业该生产线的生产效率及资源利用率。
Most research on scheduling optimization tends to solve a single LBFFSP problem for one production line,and cannot deal with the actual situation of multiple factors such as limited buffers and multiple production lines.In order to solve this problem,a basic particle swarm optimization(PSO)is proposed as a global optimization algorithm.The particle swarm algorithm based on inertia weight is cited,and the basic particle swarm algorithm is effectively prevented from falling into the local optimum by improving the algorithm.A mathematical model for optimized production scheduling of mixed-flow assembly lines with limited buffers is established to minimize production cycle and optimal buffer capacity.Take a nitrogen oxide sensor assembly line of a company as an example.Compared with the traditional method of sequencing,the results of the PSO algorithm for production sequencing can shorten the production cycle by 6.7%.The proposed sorting scheme can significantly improve the production efficiency and resource utilization of the production line of the enterprise.
作者
徐兵
杨新愉
XU Bing;YANG Xin-yu(School of Mechancial and Electrical Engineering,Changchun University of Technology,Changchun 130012,China)
出处
《组合机床与自动化加工技术》
北大核心
2021年第11期151-155,共5页
Modular Machine Tool & Automatic Manufacturing Technique
关键词
混流装配线
有限缓冲区
排产优化
粒子群算法
mixed model assembly line
limited buffer
scheduling optimization
particle swarm optimization
