Reoptimization and Self-Adjusting Price Control for Network Revenue Management

成果类型:
Article
署名作者:
Jasin, Stefanus
署名单位:
University of Michigan System; University of Michigan
刊物名称:
OPERATIONS RESEARCH
ISSN/ISSBN:
0030-364X
DOI:
10.1287/opre.2014.1297
发表日期:
2014
页码:
1168-1178
关键词:
heavy traffic analysis Asymptotic Optimality policies inventory allocation algorithm demand
摘要:
We consider a standard dynamic pricing problem with finite inventories, finite selling horizon, and stochastic demands, where the objective of the seller is to maximize total expected revenue. We introduce a simple improvement of the popular static price control known in the literature. The proposed heuristic only requires a single optimization at the beginning of the selling horizon and does not require any reoptimization at all. This provides an advantage over the potentially heavy computational burden of reoptimization, especially for very large applications with frequent price adjustments. In addition, our heuristic can be implemented in combination with a few reoptimizations to achieve a high-level revenue performance. This hybrid of real-time adjustment and reoptimization allows the seller to enjoy the benefit of reoptimization without overdoing it.
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