A Re-Solving Heuristic with Bounded Revenue Loss for Network Revenue Management with Customer Choice
A Re-Solving Heuristic with Bounded Revenue Loss for Network Revenue Management with Customer Choice
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DOI：
10.1287/moor.1120.0537
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发表时间：
2012-05
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影响因子：
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通讯作者：
Stefanus Jasin;Sunil Kumar
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文献类型：
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作者：
Stefanus Jasin;Sunil Kumar
我们考虑了客户选择和外生价格的网络收益管理问题。研究了一类确定性等价启发式控制策略的性能。这些启发式方法周期性地重新求解确定性线性规划（DLP），当所有未来的随机变量被它们的平均值取代时，结果以概率方式实现解决方案。与最优政策相比，我们提供了在这种政策下预期收入损失的上限。利用这个边界，我们构造了一个重新求解时间的时间表，使得在这些时间通过重新求解DLP并将解决方案作为概率方案实现而获得的预期收入损失由一个与问题大小无关的常数限定。
We consider a network revenue management problem with customer choice and exogenous prices. We study the performance of a class of certainty-equivalent heuristic control policies. These heuristics periodically re-solve the deterministic linear program (DLP) that results when all future random variables are replaced by their average values and implement the solutions in a probabilistic manner. We provide an upper bound for the expected revenue loss under such policies when compared to the optimal policy. Using this bound, we construct a schedule of re-solving times such that the resulting expected revenue loss, obtained by re-solving the DLP at these times and implementing the solution as a probabilistic scheme, is bounded by a constant that is independent of the size of the problem.