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Synergy-based Bidding Method for Simultaneous Freight Transportation Auctions

机译:基于协同的货运竞价竞价方法

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The tremendous use of the Internet has led freight transportation procurement websites to become an effective marketplaces that bring together several carriers and shippers. These websites enable transportation of goods in a more cost effective and safer way. From the carriers’ point of view, this situation gives rise to the bid price determination problem in an auction based fast procurement process. Carriers place bids in multiple auctions simultaneously without knowing the lanes they win until the end of the auctions. This leads to uncertainty in the calculation of the lane bid price quotes at the beginning of the auctions. Kuyzu et al. (2015) proposed a stochastic bid price optimization model for addressing the uncertainty in simultaneous procurement auctions. However, their model is a non-concave maximization problem that requires historical data and solving an exponential number of NP-Hard optimization problems. In real-life situations, several auctions may need to be priced simultaneously. In this study, we propose a simpler approach so that the bid prices can be determined simultaneously with less computational effort. We develop an efficient synergy-based method to calculate a full truckload carrier’s bid prices so that the carrier can compete with other carriers and win the tendered lanes in a profitable way. We validate the effectiveness of the synergy-based method through computational experiments involving simulations of a virtual transportation procurement auction marketplace.
机译:互联网的大量使用已使货运采购网站成为将多个承运人和托运人联系在一起的有效市场。这些网站使货物运输更具成本效益和更安全。从运营商的角度来看,这种情况在基于拍卖的快速采购流程中引起了投标价格确定问题。承运人同时在多个拍卖中进行投标,直到拍卖结束之前都不知道他们赢得的通道。这导致拍卖开始时车道竞标价格报价的不确定性。 Kuyzu等。 (2015)提出了一种随机竞标价格优化模型,以解决同时采购拍卖中的不确定性。但是,他们的模型是一个非凹面最大化问题,需要历史数据并解决指数级的NP-Hard优化问题。在现实生活中,可能需要同时对多个拍卖进行定价。在这项研究中,我们提出了一种更简单的方法,以便可以以更少的计算工作量来同时确定投标价格。我们开发了一种有效的基于协同作用的方法来计算完整的卡车承运人的投标价格,以便该承运人可以与其他承运人竞争并以有利可图的方式赢得招标路线。我们通过涉及虚拟运输采购拍卖市场模拟的计算实验,验证了基于协同作用的方法的有效性。

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