摘要
为解决汽车整车制造企业多厂区多车间联动生产下计划不准确和协调困难的问题,基于精益生产中的平准化思想对该问题进行研究,并考虑有限容量的缓冲区中库存积压或不足对生产稳定性的影响,建立了多汽车工厂协同混流排产双层规划模型。上层以最小化厂区间的转运量为目标建立跨厂区转运量分配模型,下层以最小化缓冲区中的储备偏差为目标建立车间班次选择模型。设计了双层遗传算法对该模型进行求解,并采用最小影响策略对转运量和车间产量进行标准化。通过算例将双层优化与单层优化的结果进行对比分析,并扩大算例规模。仿真实验结果表明,双层优化的求解质量更佳,从而验证了设计的模型和算法的有效性和可行性。
In order to solve the problem of inaccurate planning and coordination difficulties in the multi factory and multi workshop linkage production of automobile manufacturing enterprises,the problem was studied based on the leveling concept in lean production,considering the impact of inventory backlog or insufficient inventory in a limited capacity buffer zone on production stability.A dual level programming model for collaborative mixed flow production scheduling of multiple automobile factories was established.The upper layer establishes a cross factory transfer allocation model with the goal of minimizing the transfer volume between factories,while the lower layer establishes a workshop shift selection model with the goal of minimizing the reserve deviation in the buffer zone.A double layer genetic algorithm was designed to solve the model,and a minimum impact strategy was adopted to standardize the transportation volume and workshop output.The results of double layer optimization and single layer optimization were compared and analyzed through examples,and the scale of the examples was expanded.The simulation experiment results showed that the solution quality of double layer optimization was better,thus verifying the effectiveness and feasibility of the designed model and algorithm.
作者
杨兴臣
苌道方
YANG Xingchen;CHANG Daofang(Institute of Logistics Science and Engineering,Shanghai Maritime University,Shanghai 201306,China;College of Logistics Engineering,Shanghai Maritime University,Shanghai 201306,China)
出处
《现代制造工程》
CSCD
北大核心
2024年第8期9-18,26,共11页
Modern Manufacturing Engineering
关键词
多汽车工厂
协同混流排产
有限缓冲区
平准化
双层遗传算法
multiple automobile factories
collaborative mixed flow production scheduling
limited buffer zone
levelization
double layer genetic algorithm
