Abstract: In the current intelligent manufacturing and mixed production environment,the two-stage supply chain logistics inside and outside the core manufacturer is difficult to respond production demand synergistically and accurately.To solve this problem effectively,the characteristics of mixed production of intelligent manufacturing and logistics demand were analyzed,and a supply chain logistics synergy strategy was proposed driven by mixed production plans and composed by intelligent decision-making of delivery intervals and batch standard and delivery planning and control.The collaborative optimization model and its intelligent algorithm of two-stage material delivery intervals and batch were focused on which adapt to production takt dynamically.The collaborative optimization model of delivery intervals and batch for multi-supplier and manufacturer warehouse was established,in which the cost of supplier and manufacturer was balanced,and the complexity of multi-supplier proportional supply was considered.The optimization?objective of this model was to minimize the total cost of supply chain logistics under certain constraints,such a son-time and set delivery.The Improved multiple population genetic algorithm was adopted to achieve intelligent decision-making of optimal standard of material delivery intervals and batch.The stability and efficiency of solution for the model was improved.The validity of the research results was verified by an example application.

Key words: supply chains, logistics, coordination strategy, mixed production, intelligent manufacturing, agricultural machinery manufacturing enterprises

摘要： 为有效解决核心制造商内外两阶段供应链物流难以协同精准响应智能制造混流生产需求问题,分析了智能制造混流生产特征及其精准物流需求,提出了由混流生产计划驱动的、由物料配送期量标准及其计划控制智能决策构成的供应链物流协同策略。研究了与生产节拍动态自适应的、两阶段物料配送期量标准协同优化模型及其智能算法。均衡供应商和制造商物流成本,以两阶段供应链物流总成本为优化目标,以准时与齐套配送等为约束条件,考虑多供应商按比例供货的复杂性,构建了多供应商至制造商、制造商仓库至生产线边两阶段配送期量协同优化模型。通过改进的多种群遗传算法,实现了配送期量标准的智能优化决策,提高了模型求解的稳定性和高效性。最后通过实例验证了研究结果的有效性。

关键词: 供应链, 物流, 协同策略, 混流生产, 智能制造, 农机制造企业