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有限缓冲区下多汽车工厂协同混流排产研究OA北大核心CSTPCD

Research on collaborative mixed flow production scheduling of multiple automobile factories in a limited buffer zone

中文摘要英文摘要

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 work-shop 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 devia-tion in the buffer zone.A double layer genetic algorithm was designed to solve the model,and a minimum impact strategy was a-dopted to standardize the transportation volume and workshop output.The results of double layer optimization and single layer op-timization 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.

杨兴臣;苌道方

上海海事大学物流科学与工程研究院,上海 201306上海海事大学物流工程学院,上海 201306

计算机与自动化

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 factoriescollaborative mixed flow production schedulinglimited buffer zonelevelizationdouble layer genetic algorithm

《现代制造工程》 2024 (008)

9-18,26 / 11

10.16731/j.cnki.1671-3133.2024.08.002

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