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Optimal inventory control with sequential online auction in agriculture supply chain: an agent-based simulation optimisation approach

机译:农业供应链中具有顺序在线拍卖的最优库存控制:基于代理的仿真优化方法

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摘要

With the development of e-commerce, in agriculture supply chain, online auction is adopted as an inventory clearing tool. Comparing to mathematical models studying inventory control over online sequential auctions, our agent-based simulation model could systematically describe the complexities of bidders' information interactions and behaviour preferences caused from financial and production perspectives, and by other supply chain members. In addition, we take into account the complex and dynamic market environment, which will impact the operation effect of auction policies. With identical auction items, the profit-maximising firm must decide auction lot-size, which is the number of units in each auction, minimum initial bid, and the time interval between auctions. To obtain the optimal solution, nested partitions framework and optimal expected opportunity cost algorithm are integrated to improve computation accuracy and efficiency. A case study based on real data is conducted to implement and validate the proposed approach. Furthermore, based on the model, the paper studies the sensitivities of the decision variables under different supply and demand scenarios.
机译:随着电子商务的发展,在农业供应链中,采用在线拍卖作为库存清算工具。与研究在线顺序拍卖的库存控制的数学模型相比,我们基于代理的仿真模型可以系统地描述从财务和生产角度以及其他供应链成员所引起的投标人信息交互和行为偏好的复杂性。此外,我们考虑到复杂多变的市场环境,这将影响拍卖政策的运作效果。对于相同的拍卖项目,获利最大化的公司必须决定拍卖手的大小,即每次拍卖的单位数量,最低初始出价以及两次拍卖之间的时间间隔。为了获得最佳解决方案,将嵌套分区框架和最佳预期机会成本算法集成在一起,以提高计算精度和效率。进行了基于实际数据的案例研究,以实施和验证所提出的方法。此外,基于该模型,本文研究了在不同供求情况下决策变量的敏感性。

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