Convergence of estimated optimal inventory levels in models with probabilistic demands
DOI:
https://doi.org/10.2298/YJOR0302217BKeywords:
backorders, simulated annealing, density function estimationAbstract
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., and Korst, J., Simulated Annealing and Boltzman Machines: a Stochastic Approach to Combinatorial Optimization and Neural Computing, Wiley, N. York, 1989.
Devroye, L., and Gyorgy, L., Non Parametric Density Estimation: the L1 View, Wiley, N. York, 1985.
Faraway, J.J., and Jhun, M., "Bootstrap choice of bandwidth for density estimation", J. Amer. Statist. Ass., 85 (1990) 1119-1122.
Iyer, A.V., and Schrage, L.E., "Analysis of deterministic (s.s) inventory problems", Management Sc., 38 (1992) 1299-1313.
Jurečková, J., and Sen, P.K., Robust Statistical Procedures. Asymptotics and Interrelations. Wiley, N. York, 1996.
Lima, S., "Estudio de dos axiomatísticas para la estimación de la densidad", MSc. Thesis, Universidad de la Habana, 198.
Warrier, V., and Shah, N.H., "Probabilistic order system with a mixture of backorders and cost sales", Inv. Operacional, 18 (1997) 81-86.
Downloads
Published
Issue
Section
License
Copyright (c) 2003 YUJOR
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
