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Author: Mr.Sunil Sharma Publisher: INTERNATIONAL MONETARY FUND ISBN: 9781451859300 Category : Business & Economics Languages : en Pages : 0
Book Description
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: Mr.Sunil Sharma Publisher: INTERNATIONAL MONETARY FUND ISBN: 9781451859300 Category : Business & Economics Languages : en Pages : 0
Book Description
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: Publisher: ISBN: Category : Languages : en Pages :
Book Description
The International Monetary Fund (IMF) presents the full text of an article entitled "Optimal Inventory Policies When the Demand Distribution Is Not Known," by C. Erik Larson, Lars J. Olson, and Sunil Sharma and published November 2000. The article discusses the stochastic inventory control problem when the demand distribution is not known. A non-parametric Bayesian approach is used in which the firm's prior information is characterized by a Dirichlet process prior.
Author: James Thomas Treharne Publisher: ISBN: Category : Inventory control Languages : en Pages : 0
Book Description
This dissertation presents optimal and suboptimal procedures to solve inventory control problems that have non-stationary demand and partial information. In each period, the underlying demand distribution may change according to a known Markov process. The problem is characterized as partial information because some parameter of the demand probability distribution is not known with certainty; however, there is a known prior distribution for the unknown parameter. In one case, there is a probability density function for the demand that has at least one unknown parameter, but this parameter has a known probability distribution. In another case, there is a set of candidate demand probability distributions. The parameter which indicates which demand is in effect at any given time is unknown, but has a known probability mass function. The control strategies are adaptive because the controllers learn information about these unknown parameters over time and adapt accordingly. Because of the complexity of these problems, managers often estimate the unknown parameters and make decisions assuming the estimate is correct. The computational results presented in this dissertation demonstrate that there exist efficient and effective optimal and sub optimal procedures to solve these problems that potentially provide large cost savings compared with this current practice. The control strategies include open loop feedback and limited look ahead control for a finite horizon problem, which are compared to optimal and certainty equivalence control policies. A grid approximation and upper and lower bounds for an infinite horizon problem are also developed.
Author: Behnam Malakooti Publisher: John Wiley & Sons ISBN: 0470037326 Category : Technology & Engineering Languages : en Pages : 1114
Book Description
The first comprehensive book to uniquely combine the three fields of systems engineering, operations/production systems, and multiple criteria decision making/optimization Systems engineering is the art and science of designing, engineering, and building complex systems—combining art, science, management, and engineering disciplines. Operations and Production Systems with Multiple Objectives covers all classical topics of operations and production systems as well as new topics not seen in any similiar textbooks before: small-scale design of cellular systems, large-scale design of complex systems, clustering, productivity and efficiency measurements, and energy systems. Filled with completely new perspectives, paradigms, and robust methods of solving classic and modern problems, the book includes numerous examples and sample spreadsheets for solving each problem, a solutions manual, and a book companion site complete with worked examples and supplemental articles. Operations and Production Systems with Multiple Objectives will teach readers: How operations and production systems are designed and planned How operations and production systems are engineered and optimized How to formulate and solve manufacturing systems problems How to model and solve interdisciplinary and systems engineering problems How to solve decision problems with multiple and conflicting objectives This book is ideal for senior undergraduate, MS, and PhD graduate students in all fields of engineering, business, and management as well as practitioners and researchers in systems engineering, operations, production, and manufacturing.
Author: Jing-Sheng J. Song Publisher: Edward Elgar Publishing ISBN: 180037710X Category : Technology & Engineering Languages : en Pages : 565
Book Description
This comprehensive Handbook provides an overview of state-of-the-art research on quantitative models for inventory management. Despite over half a century’s progress, inventory management remains a challenge, as evidenced by the recent Covid-19 pandemic. With an expanse of world-renowned inventory scholars from major international research universities, this Handbook explores key areas including mathematical modelling, the interplay of inventory decisions and other business decisions and the unique challenges posed to multiple industries.
Author: Richard Ehrhardt Publisher: ISBN: Category : Computer simulation Languages : en Pages : 212
Book Description
This investigation examines the problem of managing inventory systems when the probability distributions for demand are incompletely specified. An approximately optimal (s, S) policy rule is derived, requiring knowledge of only the mean and variance of demand. The operating characteristics of the policy are found to be quite close to the characteristics of optimal policies for a wide range of parameter settings. The approximately-optimal policy rule also is examined for the situation in which the decision-maker's knowledge is limited to a sample of previously-realized demands. Policy parameters are revised periodically using a fixed number of past demands to estimate the mean and variance of the demand distribution. The importance of demand information is investigated by also analyzing the process when the mean or variance of demand is known exactly and the other parameter is periodically estimated. In addition, the research examines the accuracy of statistical forecasts that predict the future behavior of the operating characteristics. As a result, an inventory systems designer is apprised of both the costs of imperfect information and the extent of bias in the forecast estimates.
Author: G.P. Kiesmüller Publisher: BoD – Books on Demand ISBN: 3759769276 Category : Business & Economics Languages : en Pages : 384
Book Description
This book contains several topics of inventory management where the focus is on cycle and safety stocks in different situations. In order to make well-founded statements, mathematical models are used. The chosen models are simple and certainly cover only some aspects of real life. However, they are very valuable in understanding tradeoffs and identifying the essential factors affecting stock levels. Moreover, they can be used to support decision-making and optimize stock levels.
Author: Mr.Sunil Sharma
Author: Mr.Sunil Sharma
Author: C. Erik Larson
Author: 
Author: James Thomas Treharne
Author: James Thomas Treharne
Author: Behnam Malakooti
Author: Jing-Sheng J. Song
Author: Frank Herman Trinkl
Author: Richard Ehrhardt
Author: G.P. Kiesmüller