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Supply Chain Joint Inventory Management and Cost Optimization Based on Ant Colony Algorithm and Fuzzy Model

机译:基于蚁群算法和模糊模型的供应链联合库存管理与成本优化

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With the advancement of the marketization process, inventory management has transformed from a single backup protection function to an essential function for enterprises, which helps to survive and develop. Inventory control in supply chain management is the important content of supply chain management. The new management mode makes inventory management present many new characteristics and problems compared with traditional inventory management. From the view of system theory and integration theory, it is imperative to re-examine the problem of inventory control, put forward new inventory management strategies adapted to integrated supply chain management, and improve the integration of the whole supply chain, which can enhance the agility and market response speed of enterprises. Based on the in-depth study of the joint inventory management model, this paper analyzed the current situation of the joint inventory management to optimize the inventory. In view of the achievements and shortcomings of the current research, a more systematic and improved optimization model of the supply chain inventory was proposed by using the basic ideas of ant colony algorithm and fuzzy model.
机译:随着市场化进程的进步,库存管理已从单一备份保护功能转变为企业的基本功能,有助于生存和发展。供应链管理中的库存控制是供应链管理的重要内容。与传统库存管理相比,新的管理模式使库存管理显示许多新的特征和问题。从系统理论和集成理论看,必须重新研究库存控制问题,提出了适合综合供应链管理的新库存管理策略,提高整个供应链的整合,可以增强企业的敏捷和市场反应速度。基于对联合库存管理模式的深入研究,本文分析了联合库存管理的现状,以优化库存。鉴于目前研究的成就和缺点,利用蚁群算法和模糊模型的基本思路提出了一种更系统和改进的供应链库存优化模型。

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