Dynamic Inventory Management with Learning About the Demand Distribution and Substitution Probability

Li Chen; Erica L. Plambeck

doi:10.1287/msom.1070.0165

Exploring the Potential Use of the Birnbaum-Saunders Distribution in Inventory Management

Mathematical Problems in Engineering ◽

10.1155/2015/827246 ◽

2015 ◽

Vol 2015 ◽

pp. 1-9 ◽

Cited By ~ 17

Author(s):

Peter Wanke ◽

Víctor Leiva

Keyword(s):

Inventory Management ◽

Lead Time ◽

Extreme Values ◽

Lot Size ◽

Inventory Models ◽

Distributional Assumption ◽

Statistical Software ◽

Demand Distribution ◽

Gamma Distributions ◽

Potential Use

Choosing the suitable demand distribution during lead-time is an important issue in inventory models. Much research has explored the advantage of following a distributional assumption different from the normality. The Birnbaum-Saunders (BS) distribution is a probabilistic model that has its genesis in engineering but is also being widely applied to other fields including business, industry, and management. We conduct numeric experiments using the R statistical software to assess the adequacy of the BS distribution against the normal and gamma distributions in light of the traditional lot size-reorder point inventory model, known as (Q,r). The BS distribution is well-known to be robust to extreme values; indeed, results indicate that it is a more adequate assumption under higher values of the lead-time demand coefficient of variation, thus outperforming the gamma and the normal assumptions.

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Investigating Inventory Strategy Under Demand Distribution Fluctuation in Dual-Channel Supply Chain

Frontiers in Physics ◽

10.3389/fphy.2020.579652 ◽

2021 ◽

Vol 8 ◽

Author(s):

Nai-Ru Xu ◽

Jie Cheng ◽

Zheng-Qun Cai

Keyword(s):

Supply Chain ◽

Inventory Management ◽

Distribution System ◽

Demand Uncertainty ◽

Management Problem ◽

Market Demand ◽

Supply Chain System ◽

Demand Distribution ◽

Dual Channel ◽

Dual Channel Supply Chain

When manufacturers construct a dual-channel distribution system, which includes online and offline sales channels, they need to solve the inventory management problem to ensure supply and reduce inventory costs of the supply chain system. The dual-channel supply chain is the research object, and the inventory decision model is designed to achieve optimal profit when market demand is divided into online and offline demands. The results of the numerical analysis and simulations, conducted using MATLAB, indicate that both the manufacturer and the retailer increase their inventories and that their profits decrease when demand uncertainty increases. Besides, the increase in the online demand ratio causes the increase in the manufacturer’s inventory and reduces the profits of the retailer and the entire supply chain.

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On the choice of a demand distribution for inventory management models

European J of Industrial Engineering ◽

10.1504/ejie.2008.018441 ◽

2008 ◽

Vol 2 (4) ◽

pp. 479 ◽

Cited By ~ 16

Author(s):

Katrien Ramaekers ◽

Gerrit K. Janssens

Keyword(s):

Inventory Management ◽

Demand Distribution ◽

Management Models

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Developing Information Sharing Model Using Cloud Computing and Smart Devices for SMEs Supply Chain

International Journal of Information Systems and Supply Chain Management ◽

10.4018/ijisscm.2017070103 ◽

2017 ◽

Vol 10 (3) ◽

pp. 44-64 ◽

Cited By ~ 3

Author(s):

Chi-on Chan ◽

Owen Liu ◽

Ricky Szeto

Keyword(s):

Cloud Computing ◽

Supply Chain ◽

Information Sharing ◽

Size Distribution ◽

Inventory Management ◽

Supply And Demand ◽

Smart Devices ◽

Smart Device ◽

Retail Stores ◽

Demand Distribution

The mismatch between supply and demand always exists within the supply chain and among retail stores. This situation is even worse for SMEs who work without state-of-the-art technologies, especially in terms of quantitative demand and size distribution in fashion industry. In this paper, we develop a cloud computing and smart device (CCSD) model to address the stochastic deviation between supply and demand. A computational experiment proves that the performance of inventory management in the supply chain and among retail stores can be significantly improved by application of CCSD, irrespective of demand and size distribution. In this paper, we illustrate its benefits for both normal and right-skewed demand distribution. We find that different stages in supply chain can also be coordinated by using the CCSD platform. The results show that using all-channel communication network through CCSD increases the information sharing performance.

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Risk-Averse Newsboy Problem with Incomplete Demand Information

Analyzing Risk through Probabilistic Modeling in Operations Research - Advances in Logistics, Operations, and Management Science ◽

10.4018/978-1-4666-9458-3.ch014 ◽

2016 ◽

pp. 344-353

Author(s):

Bibhas Chandra Giri

Keyword(s):

Decision Maker ◽

Inventory Management ◽

Unknown Parameter ◽

Numerical Study ◽

Risk Averse ◽

Inventory Models ◽

Newsboy Problem ◽

Common Assumption ◽

Demand Distribution ◽

Demand Information

In the traditional inventory management literature, it is a quite common assumption that the probability distribution of stochastic demand is completely known to the decision maker. However, in reality, there are ample evidences where the demand distribution is not known with certainty. In order to cope with the practical situation, it is, therefore, necessary to investigate inventory models with available incomplete information. This chapter is aimed to study a simple single-period newsboy problem in which the decision maker is risk-averse and the demand information is not perfectly known to him/her. We derive a forecast cost for the period based on sample observation used to set the value of an unknown parameter of the distribution. We analyze the significance of risk aversion on the optimal decisions. From numerical study, we observe that the expected forecast cost increases when less information about demand is available and that the risk-averse inventory manager incurs higher cost than risk-neutral manager.

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