Adaptive Ordering and Pricing for Perishable Products

References

• Abad P. L. Optimal pricing and lot-sizing under conditions of perishability and partial backordering. Management Sci. (1996) 42:1093–1104Link, Google Scholar
• Azoury K. S. Bayes solutions to dynamic inventory models under unknown demand distribution. Management Sci. (1985) 31:1150–1160Link, Google Scholar
• Benveniste A., Métivier M., Priouret P.Adaptive Algorithms and Stochastic Approximations (1990) (Springer-Verlag, New York) Crossref, Google Scholar
• Braden D., Freimer M. Informational dynamics of censored observations. Management Sci. (1991) 37:1390–1404Link, Google Scholar
• Burnetas A. N., Katehakis M. N. Optimal adaptive policies for sequential allocation problems. Adv. App. Math. (1996) 17:122–142Crossref, Google Scholar
• Eliashberg J., Steinberg R., Eliashberg J., Lillien G. L. Marketing-production joint decision making. Handbooks in Operations Research and Management Science. Marketing Vol. 5. (1993) (Elsevier Science Publishers)Google Scholar
• Ermoliev Yu. M. Stochastic quasigradient methods and their application to systems optimization. Stochastics (1983) 9:1–36Crossref, Google Scholar
• Gallego G., Moon I. The distribution free newsboy problem: Review and extensions. J. Oper. Res. Soc. (1993) 44:825–834Crossref, Google Scholar
• Gallego G., Van Ryzin G. Optimal dynamic pricing of inventories with stochastic demand over finite horizons. Management Sci. (1994) 40:999–1020Link, Google Scholar
• Katehakis M. N., Robbins H. Sequential allocation from several populations. Proc. Natl. Acad. Sci. USA (1995) 92(19):8584Crossref, Google Scholar
• Kushner H., Ying G.Stochastic Approximation Algorithms and Applications (1997) (Springer-Verlag, New York) Crossref, Google Scholar
• Lai T. L., Robbins H. Consistency and asymptotic efficiency of slope estimates in stochastic approximation schemes. Z. Wahrscheinlichkeitstheorie verw. Geb. (1981) 56:329–360Crossref, Google Scholar
• Lai T. L., Robbins H. Asymptotically efficient adaptive allocation rules. Adv. App. Math. (1985) 6:4–22Crossref, Google Scholar
• Lariviere M. A., Porteus E. L. Informational dynamics and new product pricing. (1995) . Technical report. Stanford Graduate School of Business, Stanford University, Stanford, CAGoogle Scholar
• Loève M.Probability Theory II (1978) 4th ed.(Springer-Verlag)Crossref, Google Scholar
• Lovejoy W. S. Myopic policies for some inventory models with uncertain demand distributions. Management Sci. (1990) 36:724–738Link, Google Scholar
• Nahmias S. Demand estimation in lost sales inventory systems. Naval Res. Logist. Quart. (1994) 41:739–757Crossref, Google Scholar
• Rajan A., Steinberg Rakesh R. Dynamic pricing and ordering decisions by a monopolist. Management Sci. (1992) 38:240–262Link, Google Scholar
• Robbins H. Some aspects of the sequential design of experiments. Bull. Amer. Math. Monthly (1952) 58:527–536Crossref, Google Scholar
• Robbins H., Monro S. A stochastic approximation method. Ann. Math. Statist. (1951) 22:400–407Crossref, Google Scholar
• Robbins H., Siegmund D., Rustagi J. A convergence theorem for nonnegative almost supermartingales and some applications. Optimization Methods in Statistics (1971) (Academic Press, New York) 233–257Google Scholar
• Scarf H., Arrow K., Karlin S., Scarf H. A min-max solution of an inventory problem. Studies in the Mathematical Theory of Inventory and Production (1958) (Stanford University Press, Stanford, CA) 201–209Google Scholar
• Silver E. Bayesian updating of an arbitrary discrete distribution under a special case of partial information. Commun. Statist.-Stochastic Models (1993) 9(4):615–638Crossref, Google Scholar
• Vairaktarakis G. Robust newsboy models with budget constraints. Internat. J. Prod. Econom. (2000) . forthcomingCrossref, Google Scholar