Optimal inventory control with sequential online auction in agriculture supply chain: an agent-based simulation optimisation approach
针对农业供应链中采用在线拍卖清库存的问题，构建了基于智能体的仿真模型，考虑竞标者信息交互和行为偏好，优化拍卖批量、最低起拍价和拍卖间隔，并通过真实数据案例验证。
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.