Convergence of estimated optimal inventory levels in models with probabilistic demands

Authors

  • Carlos N. Bouza Departamento de Matematica Aplicada Facultad de Matematica y Computacion Universidad de La Haban

DOI:

https://doi.org/10.2298/YJOR0302217B

Keywords:

backorders, simulated annealing, density function estimation

Abstract

The behavior of estimations of the optimal inventory level is analyzed. Two models are studied. The demands follow unknown probability distribution function. The included density functions are estimated and a plug-in rule is suggested for computing estimates of the optimal levels. Two search algorithms are proposed and compared using Monte Carlo experiments. .

References

Aarts, E., Korst, J. (1989) Simulated annealing and Boltzmann machines: A stochastic approach to combinatorial optimization and neural computing. New York, itd: Wiley

Devroye, L., Gyorgy, L. (1985) Non parametric density estimation: The L1 view. New York, itd: Wiley

Faraway, J.J., Jhun, M. (1990) Bootstrap choice of bandwidth for density estimation. Journal of the American Statistical Association, 85, 412, 1119-1122

Iyer, A.V., Schrage, L.E. (1992) Analysis of deterministic (s. s) inventory problems. Management Science, 38, 1299-1313

Jurečkova, J., Sen, P.K. (1996) Robust statistical procedures. Asymptotic and interrelations. New York, itd: Wiley

Lima, S. Estudio de dos axiomaticas para la estimacion de la densidad. Universidad de la Habana, MSc. Thesis, 198

Warrier, V., Shah, N.H. (1997) Probabilistic order level system with a mixture of backorders and lost sales. Investigacion Oper., 18, 3, 81-85

Downloads

Published

2003-09-01

Issue

Vol. 13 No. 2 (2003)

Section

Research Articles

License

Copyright (c) YUJOR

Creative Commons License

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.