Author : A. Dvoretzky
Publisher :
Page : 12 pages
File Size : 17,63 MB
Release : 1957
Category : Inventory control
ISBN :
Loss functions are given for which there exist optimal two-level ordering policies (s,S) in one-stage inventory problems with an arbitrarily specified distribution of demand.
Author : A. Dvoretzky
Publisher :
Page : 10 pages
File Size : 19,79 MB
Release : 1957
Category : Inventory control
ISBN :
Loss functions are given for which there exist optimal two-level ordering policies (s, S) in one-stage inventory problems with an arbitrarily specified distribution of demand.
Author : Arthur F. Veinott (Jr.)
Publisher :
Page : 50 pages
File Size : 27,54 MB
Release : 1964
Category : Inventories
ISBN :
Author : Arthur F Veinott (Jr)
Publisher :
Page : 30 pages
File Size : 15,46 MB
Release : 1965
Category :
ISBN :
Scarf has shown that the (s, S) policy is optimal for a class of discrete review dynamic nonstationary inventory models. In this paper a new proof of this result is found under new conditions which do not imply and are not implied by Scarf's hypotheses. We replace Scarf's hypothesis that the one period expected costs are convex by the weaker assumption that the negative of these expected costs are unimodal. In addition, the bounds on the optimal parameter values given by Veinott and Wagner are established for the present case. The bounds in a period are easily computed, and depend only upon the expected costs for that period. Moreover, simple conditions are given which ensure that the optimal parameter values in a given period equal their lower bounds. This result is exploited to derive a planning horizon theorem. (Author).
Author : Suresh Sethi
Publisher :
Page : 0 pages
File Size : 34,92 MB
Release : 2014
Category :
ISBN :
This paper is concerned with a generalization of classical inventory models (with fixed ordering costs) that exhibit (s, S) policies. In our model, the distribution of demands in successive periods is dependent on a Markov chain. The model includes the case of cyclic or seasonal demand. The model is further extended to incorporate some other realistic features such as no ordering periods and storage and service level constraints. Both finite and infinite horizon nonstationary problems are considered. We show that (s, S) policies are also optimal for the generalized model as well as its extensions.
Author : A. Dvoretzky
Publisher :
Page : 36 pages
File Size : 35,8 MB
Release : 1952
Category : Mathematical statistics
ISBN :
Author : Feng Cheng
Publisher :
Page : 0 pages
File Size : 12,52 MB
Release : 2009
Category :
ISBN :
Markov-modulated processes have been used in stochastic inventory models with setup costs for modeling demand under the influence of uncertain environmental factors, such as fluctuating economic and market conditions. The analyses of these models have been carried out in the literature only under the assumption that unsatisfied demand is fully backlogged. The lost sales situation occurs in many retail establishments such as department stores and supermarkets. We use the analysis of the Markovian demand model with backlogging to analyze the lost sales case; in particular, we establish the optimality of an (s, S)-type policy under fairly general conditions.
Author : Lakdere Benkherouf
Publisher :
Page : 0 pages
File Size : 30,77 MB
Release : 2019
Category :
ISBN :
This note is concerned with the optimality of an (s; S) policy for a single-item infinite-horizon inventory model when the penalty cost is made-up of two parts: A lump-sum cost independent of the amount of the shortage and a variable cost proportional to the amount of the shortage. Using a Quasi-Variational Inequality (QVI) approach, an (s; S) policy is shown to be optimal under some mild technical conditions.
Author : Mr.Sunil Sharma
Publisher : INTERNATIONAL MONETARY FUND
Page : 0 pages
File Size : 30,52 MB
Release : 2000-11-01
Category : Business & Economics
ISBN : 9781451859300
This paper analyzes the stochastic inventory control problem when the demand distribution is not known. In contrast to previous Bayesian inventory models, this paper adopts a non-parametric Bayesian approach in which the firm’s prior information is characterized by a Dirichlet process prior. This provides considerable freedom in the specification of prior information about demand and it permits the accommodation of fixed order costs. As information on the demand distribution accumulates, optimal history-dependent (s,S) rules are shown to converge to an (s,S) rule that is optimal when the underlying demand distribution is known.
Author : Dimitri P. Bertsekas
Publisher :
Page : 323 pages
File Size : 23,20 MB
Release : 1961
Category : Dynamic programming
ISBN : 9780120932603
