整车运输协作问题迭代拍卖机制设计

Iterative auction design for truckload collaborative transportation

实践中,很多企业已经参与了由第三方物流平台组织和协调的整车协作运输项目,以提高利润.本文提出了不完全信息条件下多个运输商在整车运输方面协作的迭代拍卖机制.本文为该机制设计了一种简便的算法,其中各运输商在每一轮拍卖中只需求解线性规划模型进行竞标,且算法在匹配时最优确定各运输商的买家或卖家角色.本文证明了该机制同时满足防范操纵性,个体理性,预算平衡性,单调性,和有限收敛性.大量数值实验表明该机制具有很高的有效性,并能显著地增加各运输商的个体利润.实验还发现当运输网络规模更大,运输商平均拥有的线路数量较小,各运输商运营成本存在较大差异时,该机制的性能一般也会更好.

In practices, many freight transportation companies have participated in collaborative shipping programs organized by third-party logistics platforms, in order to improve their profits. In this paper, we design an iterative auction mechanism for truckload carriers’ collaboration under incomplete information.We develop an easy algorithm to implement this mechanism, where each carrier only solves linear programs for bidding bundles and the mechanism optimally assigns the roles of seller or buyer to the carriers. We prove that the iterative auction mechanism simultaneously satisfies strategy-proofness, individual rationality, budget balance, monotonicity, and finite convergence. Extensive computational experiments show that the mechanism is highly efficient and substantially increases the carriers’ individual profits. The experiments also find that the mechanism typically performs better when the transportation network scale is larger, the average number of lanes initially owned by carriers is smaller, and the operational cost efficiency of carriers is more heterogeneous.