Toward Robust Revenue Management: Competitive Analysis of Online Booking
In this paper, we consider the revenue management problem from the perspective of online algorithms. This approach eliminates the need for both demand forecasts and a risk-neutrality assumption. The competitive ratio of a policy relative to a given input sequence is the ratio of the policy's pe...
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| Published in: | Operations research Vol. 57; no. 4; pp. 950 - 963 |
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| Main Authors: | , |
| Format: | Journal Article |
| Language: | English |
| Published: |
Hanover, MD
INFORMS
01.07.2009
Institute for Operations Research and the Management Sciences |
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| ISSN: | 0030-364X, 1526-5463 |
| Online Access: | Get full text |
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| Abstract | In this paper, we consider the revenue management problem from the perspective of online algorithms. This approach eliminates the need for both demand forecasts and a risk-neutrality assumption. The competitive ratio of a policy relative to a given input sequence is the ratio of the policy's performance to the offline optimal. Under the online algorithm approach, revenue management policies are evaluated based on the highest competitive ratio they can guarantee. We are able to define lower bounds on the best-possible performance and describe policies that achieve these lower bounds. We address the two-fare problem in greatest detail, but also treat the general multifare problem and the bid-price control problem. |
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| AbstractList | In this paper, we consider the revenue management problem from the perspective of online algorithms. This approach eliminates the need for both demand forecasts and a risk-neutrality assumption. The competitive ratio of a policy relative to a given input sequence is the ratio of the policy's performance to the offline optimal. Under the online algorithm approach, revenue management policies are evaluated based on the highest competitive ratio they can guarantee. We are able to define lower bounds on the best-possible performance and describe policies that achieve these lower bounds. We address the two-fare problem in greatest detail, but also treat the general multifare problem and the bid-price control problem. In this paper, we consider the revenue management problem from the perspective of online algorithms. This approach eliminates the need for both demand forecasts and a risk-neutrality assumption. The competitive ratio of a policy relative to a given input sequence is the ratio of the policy's performance to the offline optimal. Under the online algorithm approach, revenue management policies are evaluated based on the highest competitive ratio they can guarantee. We are able to define lower bounds on the best-possible performance and describe policies that achieve these lower bounds. We address the two-fare problem in greatest detail, but also treat the general multifare problem and the bid-price control problem. [PUBLICATION ABSTRACT] |
| Audience | Trade |
| Author | Queyranne, Maurice Ball, Michael O |
| Author_xml | – sequence: 1 fullname: Ball, Michael O – sequence: 2 fullname: Queyranne, Maurice |
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| Cites_doi | 10.1016/S0377-2217(95)00328-2 10.1007/b139000 10.1287/opre.1070.0486 10.1007/PL00011380 10.1287/trsc.21.2.63 10.1287/opre.1030.0065 10.1016/S0925-5273(99)00129-2 10.1287/mnsc.49.10.1363.17316 10.1287/opre.37.2.183 10.1287/mnsc.46.6.760.11936 10.1287/trsc.33.2.136 10.1287/trsc.27.3.252 10.1287/mnsc.1080.0859 10.1287/opre.41.1.127 10.1145/335305.335385 10.1007/s10107-003-0436-0 10.1287/trsc.33.2.233 10.1287/mnsc.1030.0147 |
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| Keywords | Lower bound Competitiveness Booking Return rate Real time analysis of algorithms: suboptimal algorithms Production management inventory/production: policies, marketing/pricing Pricing Price control Inventory control Marketing policy Tariffication Algorithm analysis |
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| SubjectTerms | Airline industry Airlines Algorithms Analysis analysis of algorithms Applied sciences Control theory Determinism Emergency protective orders Exact sciences and technology Firm modelling Inventory control, production control. Distribution inventory/production marketing/pricing Mathematical sequences Online transaction processing Operational research and scientific management Operational research. Management science Order quantity policies Pricing Pricing policies Probability distributions Regret Reservation systems Revenue Revenue management Studies suboptimal algorithms Wage & price controls |
| Title | Toward Robust Revenue Management: Competitive Analysis of Online Booking |
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