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OR Spectrum
Erschienen in: OR Spectrum 1/2007

01.01.2007 | Regular Article

Simulation of stochastic demand data streams for network revenue management problems

verfasst von: Alf Kimms, Michael Müller-Bungart

Erschienen in: OR Spectrum | Ausgabe 1/2007

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Abstract

For evaluating heuristic and optimal network revenue management procedures test-instances are needed. As a consequence when trying to create instances for network revenue management problems it turns out that among other things a stream of stochastic demand data is required. But, developing and implementing a generator for demand data that fits to a given network, a given set of products, and a given set of capacity constraints is far from being easy. Since to the best of our knowledge no such demand data generator is available to the public, we specify an algorithm to generate this data and we also make this algorithm available upon request. This, we hope, facilitates future research work.
Vorheriger Artikel Revenue management
Nächster Artikel Simulation optimization for revenue management of airlines with cancellations and overbooking

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Literatur
Barr RS, Golden BL, Kelly JP, Resende MGC, Stewart WR (1995) Designing and reporting on computational experiments with heuristic methods. J Heuristics 1:9–32CrossRef
Beckmann MJ, Bobkoski F (1958) Airline demand: an analysis of some frequency distributions. Nav Res Logist Q 5:43–51
Belobaba PP (1989) Application of a probabilistic decision model to airline seat inventory control. Oper Res 37:183–197
Bertsimas D, de Boer S (2005) Simulation-based booking limits for airline revenue management. Oper Res 53:90–106 CrossRef
Bertsimas D, Popescu I (2003) Revenue management in a dynamic network environment. Transp Sci 37:257–277CrossRef
Bitran GR, Gilbert SM (1996) Managing hotel reservations with uncertain arrivals. Oper Res 44:35–49
Bitran GR, Mondschein SV (1995) An application of yield management to the hotel industry considering multiple day stays. Oper Res 43:427–443
Bratley P, Bennett L, Schrage LE (1987) A guide to simulation, 2nd edn., Springer, Berlin Heidelberg New York
Brumelle SL, McGill JI (1993) Airline seat allocation with multiple nested fare classes. Oper Res 41:127–137
Chan LMA, Simchi Levi D, Swann J (2001) Dynamic pricing strategies for manufacturing with stochastic demand and discretionary sales. Working Paper, Georgia Institute of Technology
Chen D (1998) Network Flows in Hotel Yield Management. Working Paper TR1225, Cornell University
Coughlan J (1999) Airline overbooking in the multi–class case. J Oper Res Soc 50:1098–1103CrossRef
Curry RE (1990) Optimal airline seat allocation with fare classes nested by origins and destinations. Transp Sci 41:193–204
de Boer S, Freling R, Piersma N (2002) Mathematical programming for network revenue management revisited. Eur J Oper Res 137:72–92CrossRef
DeGroot MH (1970) Optimal statistical decisions. McGraw-Hill, New York
Dror M, Trudeau P, Ladany SP (1988) Network models for seat allocation on flights. Transp Res 22B:239–250CrossRef
Elimam AA, Dodin BM (2001) Incentives and yield management in improving productivity of manufacturing facilities. IIE Trans 33:449–462
Gallego G, van Ryzin G (1994) Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Manage Sci 40:999–1020
Gallego G, van Ryzin G (1997) A multiproduct dynamic pricing problem with applications to network yield management. Oper Res 45:24–41
Glover F, Glover R, Lorenzo J, McMillan C (1982) The passenger mix problem in the scheduled airlines. Interfaces 12:73–79
Goldman P, Freling R, Pak K, Piersma N (2001) Models and techniques for hotel revenue management using a rolling horizon. Working Paper, Erasmus University, Rotterdam
Grandell J (1997) Mixed Poisson processes. Chapman and Hall, London
Günther DP, Chen VCP, Johnson EL (1999) Yield management: optimal bid prices for single-hub problems without cancellations. Working Paper, Georgia Institute of Technology
Hersh M, Ladany SP (1978) Optimal seat allocation for flights with one intermediate stop. Comput Oper Res 5:31–37CrossRef
Kimms A, Klein R (2005) Revenue Management im Branchenvergleich. Z Betr wirtsch Erg h 1:1–30
Klein R (2004) Private communication as having been supervisor of Miklitz (2003)
Knuth DE (1998) The art of computer programming: 2. Seminumerical algorithms, 3rd edn., Addison–Wesley, Boston
Kolisch R, Sprecher A, Drexl A (1995) Characterization and generation of a general class of resource–constrained project scheduling problems. Manage Sci 41:1693–1703
Ladany SP (1976) Dynamic operating rules for motel reservations. Decis Sci 7:829–840
Ladany SP (2001) Optimal hotel segmentation mix strategy. Int J Serv Technol Manag 2:18–27CrossRef
Ladany SP, Arbel A (1991) Optimal cruise–liner passenger cabin pricing policy. Eur J Oper Res 55:136–147CrossRef
Ladany SP, Bedi DN (1977) Dynamic booking rules for flights with an intermediate stop. Omega 5:721–730CrossRef
Ladany SP, Chou FS (2001) Optimal yield policy with infiltration consideration. Int J Serv Technol Manag 2:4–17CrossRef
Lautenbacher CJ, Stidham S (1999) The underlying Markov decision process in the single-leg airline yield—management problem. Transp Sci 33:136–146
Law AM, Kelton WD (2000) Simulation modelling and analysis, 3rd edn., McGraw-Hill, Boston
L'Ecuyer P (1999) Good parameters and implementations for combined multiple recursive random number generators Oper Res 47:159–164
L'Ecuyer P, Simard R, Chen EJ, Kelton WD (2002) An object–oriented random–number package with many long streams and substreams. Oper Res 50:1073–1075CrossRef
Lee AO (1990) Airline reservations forecasting: probabilistic and statistical models of the booking Process. Ph.D. dissertation, MIT
Lee TC, Hersh M (1993) A model for dynamic airline seat inventory control with multiple seat bookings. Transp Sci 27:252–265
Lewis PAW, Shedler GS (1979) Simulation of nonhomogeneous Poisson processes by thinning. Nav Res Logist Q 26:403–413
Littlewood K (1972) Forecasting and control of passenger bookings. AGIFORS Symposium Proceedings.
Lyle C (1970) A statistical analysis of the variability in aircraft occupancy. AGIFORS Symposium Proceedings
Marsaglia G, Tsang WW (2000) A simple method for generating gamma variables. ACM Trans Math Softw 26:363–372CrossRef
Metters R, Vargas V (1999) Yield management for the nonprofit sector. J Serv Res 1:215–226
Miklitz T (2003) Preis–Mengen–Steuerung im Revenue Management. Diploma Thesis, Technical University Darmstadt
Pak K, Dekker R (2004) Cargo revenue management: bid-prices for a 0–1 multi Knapsack problem. Working Paper, Erasmus University Rotterdam
Press WH, Teukolsky SA, Vetterling WT, Flannery BP (1993) Numerical recipes in C—the art of scientific computing, 2nd edn., Cambridge University Press, Cambridge
Pugh GR (2004) An analysis of the Lanczos Gamma Approximation. Ph.D. Thesis, University of British Columbia
Richter H (1982) The differential revenue method to determine optimal seat allotments by fare type. AGIFORS Symposium Proceedings
Robinson LW (1995) Optimal and approximate control policies for airline booking with sequential nonmonotonic fare classes. Oper Res 43:252–263
Ross SM (2000) Introduction to probability models. 7th edn., San Diego, Harcourt
Rothstein M (1971) An airline overbooking model. Transp Sci 5:180–192
Stuart A, Ord JK (1987) Kendall's advanced theory of statistics. 1: Distribution theory, 5th edn., Charles Griffin & Co., London
Subramanian J, Stidham SJ, Lautenbacher CJ (1999) Airline yield management with overbooking, cancellations, and no–shows. Transp Sci 33:147–167
Swan WM (2002) Airline demand distributions: passenger revenue management and spill. Transp Res 38E:253–263
Talluri KT, van Ryzin GJ (1998) An analysis of bid–price controls for network revenue management. Manage Sci 44:1577–1593
Talluri KT, van Ryzin GJ (1999) A randomized linear programming method for computing network bid prices. Transp Sci 33:207–216
Talluri KT, van Ryzin GJ (2004) The theory and practice of revenue management. Boston, Kluwer
van Ryzin GJ, McGill J (2000) Revenue management without forecasting or optimization: an adaptive algorithm for determining seat protection levels. Manage Sci 42:760–775CrossRef
Weatherford LR, Bodily SE, Pfeiffer PE (1993) Modelling the customer arrival process and comparing decision rules in perishable asset revenue management situations. Transp Sci 27:239–251CrossRef
Wollmer RD (1992) An airline seat management model for a single leg route when lower fare classes book first. Oper Res 40:26–37
You P-S (2003) Dynamic pricing of inventory with cancellation demand. J Oper Res Soc 54:1093–1101CrossRef
Zhao W, Zheng YS (1998) Optimal dynamic capacity allocation with multi–class nonstationary demand. Working Paper, Wharton School
Metadaten
Titel
Simulation of stochastic demand data streams for network revenue management problems
verfasst von
Alf Kimms
Michael Müller-Bungart
Publikationsdatum
01.01.2007
Verlag
Springer-Verlag
Erschienen in
OR Spectrum / Ausgabe 1/2007
Print ISSN: 0171-6468
Elektronische ISSN: 1436-6304
DOI
https://doi.org/10.1007/s00291-005-0020-5

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