Decision support for truckload carriers in one-shot combinatorial auctions
Decision support for truckload carriers in one-shot combinatorial auctions
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DOI：
10.1016/j.trb.2008.09.003
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发表时间：
2009-06
影响因子：
6.8
通讯作者：
Tsung-Sheng Chang
中科院分区：
文献类型：
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作者：
Tsung-Sheng Chang
组合拍卖已成为托运人获得运输服务的流行方式。然而，在组合拍卖中，卡车承运商很难解决投标产生和评标问题。本文的目标是开发一个竞标顾问，以帮助载货运输公司克服一次组合拍卖中这些具有挑战性的问题。建议的顾问将电子市场中的负载信息与运营商当前的车队管理计划集成在一起，然后选择理想的负载包。本文通过提出的近似估计负荷间的平均协同值，将一次组合拍卖中TL运营商的报价生成和评估问题化为协同最小成本流问题。求解最小代价流问题的传统求解方法不适用于协同网络流问题。因此，我们提出了一种列生成方法来解决这个特定的网络流问题。本文的主要贡献在于，采用建议的顾问的TL运营商可以很容易地确定理想的出价包，而无需评估所有2n−1个可能的负载束，其中n是负载的数量。
Combinatorial auctions have become popular for shippers to secure transportation services. It is, however, very difficult for truck carriers to solve bid generation and evaluation problems in combinatorial auctions. The objective of this paper is to develop a bidding advisor to help truckload (TL) carriers overcome such challenging problems in one-shot combinatorial auctions. The proposed advisor integrates the load information in e-marketplaces with carriers’ current fleet management plans, and then chooses the desirable load bundles. In this paper, a TL carrier’s bid generation and evaluation problems in one-shot combinatorial auctions are formulated as a synergetic minimum cost flow problem by estimating the average synergy values between loads through the proposed approximation. The conventional solution approaches for solving the minimum cost flow problems cannot be applied to the synergetic network flow problem. Thus, we propose a column generation approach to solve this specific network flow problem. The main contribution of this paper is that a TL carrier adopting the proposed advisor can easily determine the desirable bid packages without evaluating all 2n−1 possible bundles of loads, where n is the number of loads.