Journal of Revenue and Pricing Management

, Volume 10, Issue 2, pp 105–111 | Cite as

Golf course revenue management

  • Lila Rasekh
  • Yihua Li
Practice Article
First Online:
Received:
Revised:

Abstract

This research is based on an analysis of golf course tee-time reservation practice. Specifically, this article presents a unique linear model that can be used to assign the demand to the available tee-times, and thus, maximize their utilization and the total revenue. The model is solved by using the SAS-OR built-in branch and bound (B&B) algorithm. To reduce the computational time, we propose a heuristic to find an initial feasible solution to the model. This initial solution reduces the CPU time substantially and enabled us to solve the larger-scale problem by using the SAS-OR.

Keywords

revenue management golf course demand optimization SAS-OR branch and bound 
This is a preview of subscription content, log in to check access.

References

  1. Barnhart, C., Farahat, A. and Lohatepanont, M. (2009) Airline fleet assignment with enhanced revenue modeling. Operations Research 57: 231–244.CrossRefGoogle Scholar
  2. Barnhart, C., Kniker, T. and Lohatepanont, M. (2002) Itinerary-based airline fleet assignment. Transportation Science 36: 199–217.CrossRefGoogle Scholar
  3. Belobaba, P. (1987) Airline yield management: An overview of seat inventory control. Transportation Science 21: 63–73.CrossRefGoogle Scholar
  4. Bertsimas, D. and Popescu, I. (2003) Revenue management in a dynamic network environment. Transportation Science 37: 257–277.CrossRefGoogle Scholar
  5. Bitran, G.R. and Gilbert, S.M. (1996) Managing hotel reservations with uncertain arrivals. Operations Research 44: 35–49.CrossRefGoogle Scholar
  6. Bitran, G.R. and Mondschein, S.V. (1995) An application of yield management to the hotel industry considering multiple day stays. Operations Research 43: 427–443.CrossRefGoogle Scholar
  7. Feng, Y. and Xiao, B. (2000) A continuous-time yield management model with multiple prices and reversible price changes. Management Science 46: 644–657.CrossRefGoogle Scholar
  8. Gallego, G. and van Ryzin, G. (1997) A multi-product dynamic pricing problem and its applications to network yield management. Operations Research 45: 24–41.CrossRefGoogle Scholar
  9. Geoffrion, A.M. and Marsten, R.E. (1972) Integer programming algorithms: A framework and state-of-the-art survey. Management Science 18 (9): 465–491.CrossRefGoogle Scholar
  10. Hadjer, A., Marcotte, O. and Soumis, F. (2006) A branch-and-cut algorithm for the multiple depot vehicle scheduling problem. Operations Research 54: 130–149.CrossRefGoogle Scholar
  11. Held, M. and Karp, R.M. (1970) Traveling salesman problem and minimal spanning trees. Operations Research 18: 1138–1162.CrossRefGoogle Scholar
  12. Kimes, S.E. and Schruben, L.W. (2002) Golf course revenue management: A study of tee time intervals. Journal of Revenue and Pricing Management 1 (2): 111–120.CrossRefGoogle Scholar
  13. Li, Y. and Wang, X. (2005) Integration of fleet assignment and aircraft routing. Transportation Research Record 1915: 79–84.Google Scholar
  14. Li, Y., Wang, X. and Adams, T. (2009) Ride service outsourcing for profit maximization. Transportation Research Part E 45: 138–148.CrossRefGoogle Scholar
  15. Liang, Y. (1999) Solution to the continuous time dynamic yield management model. Transportation Science 33: 117–123.CrossRefGoogle Scholar
  16. Talluri, K.T. and Van Ryzin, G.J. (2005) The Theory and Practice of Revenue Management. New York, USA: Springer.Google Scholar
  17. Wang, X. and Meng, Q. (2008) Continuous time revenue management with demand driven dispatch in the airlines industry. Transportation Research Part E 44 (6): 1052–1073.CrossRefGoogle Scholar

Copyright information

© Palgrave Macmillan, a division of Macmillan Publishers Ltd 2009

Authors and Affiliations

  • Lila Rasekh
    • 1
  • Yihua Li
    • 1
  1. 1.Revenue Management, Walt Disney World Co.OrlandoUSA

Personalised recommendations