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Accelerating Vickrey Payment Computation in Combinatorial Auctions for an Airline Alliance

机译:加速Vickrey支付计算在航空公司联盟的组合拍卖中

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Among all the variations of general combinatorial auctions, the Vickrey auction is essentially the only incentive-compatible auction. Furthermore, it is individual rational and weakly budget-balanced. In many cases these properties are very desirable. However, computing the winners and their payments in a Vickrey auction involves solving several NP-complete problems. While there have been many approaches to solve the winner determination problem via search, this search has not been extended to compute the Vickrey payments. The naive approach is to consecutively solve each problem using the same search algorithm. We present an extension to this procedure to accelerate the computation of Vickrey payments using a simple backtrack algorithm. However, our results can be applied to sophisticated branch-and-bound solvers as well. We test our approach on data evolving from a Lufthansa flight schedule. Data of this type might be of interest, since authentic data for combinatorial auctions is rare and much sought after. A remarkable result is that after solving the winner determination problem we can provide bounds for the remaining problems that differ from the optimal solution by only 2.2% on average. We as well manage to obtain a rapid speedup by tolerating small deviations from the optimal solutions. In all cases, the actual deviations are much smaller than the allowed deviations.
机译:在一般组合拍卖的所有变体中,Vickrey拍卖基本上是唯一的激励兼容拍卖。此外,它是个人理性和弱预算平衡。在许多情况下,这些属性非常可取。但是,计算获奖者及其在Vickrey拍卖中的付款涉及解决几个NP完整问题。虽然通过搜索解决了许多方法来解决获胜者确定问题,但该搜索尚未扩展到计算Vickrey付款。天真的方法是使用相同的搜索算法连续解决每个问题。我们向此过程提出了扩展,以加速使用简单的回溯算法计算Vickrey付款。但是,我们的结果也可以应用于复杂的分支和结合的溶剂。我们在汉莎航班计划中测试了我们的方法。这种类型的数据可能是有意义的,因为组合拍卖的真实数据很少,并且追求了很多。显着的结果是,在解决胜利者的确定问题后,我们可以为剩余问题提供与平均只有2.2%不同的剩余问题的界限。我们并管理通过容忍来自最佳解决方案的小偏差来获得快速加速。在所有情况下,实际偏差远小于允许的偏差。

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