The Young Professional Dream Company's Stochastic Inventory Management Problem

2016 ◽  
Author(s):  
Wenbo Cai ◽  
Layek Abdel-Malek
2018 ◽  
Vol 200 ◽  
pp. 00013 ◽  
Author(s):  
Nouçaiba Sbai ◽  
Abdelaziz Berrado

Inventory management remains a key challenge in supply chain management. Many companies recognize the benefits of a good inventory management system. An effective inventory management helps reaching a high customer service level while dealing with demand variability. In a complex supply chain network where inventories are found across the entire system as raw materials or finished products, the need for an integrated approach for managing inventory had become crucial. Modelling the system as a multi-echelon inventory system allows to consider all the factors related to inventory optimization. On the other hand, the high criticality of the pharmaceutical products makes the need for a sophisticated supply chain inventory management essential. The implementation of the multi-echelon inventory management in such supply chains helps keeping the stock of pharmaceutical products available at the different installations. This paper provides an insight into the multi-echelon inventory management problem, especially in the pharmaceutical supply chain. A classification of several multi-echelon inventory systems according to a set of criteria is provided. A synthesis of multiple multi-echelon pharmaceutical supply chain problems is elaborated.


Mathematics ◽  
2019 ◽  
Vol 7 (1) ◽  
pp. 75 ◽  
Author(s):  
Suman Maity ◽  
Sujit Kumar De ◽  
Sankar Prasad Mondal

The present article was developed for the economic order quantity (EOQ) inventory model under daytime, non-random, uncertain demand. In any inventory management problem, several parameters are involved that are basically flexible in nature with the progress of time. This model can be split into three different sub-models, assuming the demand rate and the cost vector associated with the model are non-randomly uncertain (i.e., fuzzy), and these may include some of the retained learning experiences of the decision-maker (DM). However, the DM has the option of revising his/her decision through the application of the appropriate key vector of the fuzzy locks in their final state. The basic novelty of the present model is that it includes a computer-based decision‐making process involving flowchart algorithms that are able to identify and update the key vectors automatically. The numerical study indicates that when all parameters are assumed to be fuzzy, the double keys of the fuzzy lock provide a more accurate optimum than other methods. Sensitivity analysis and graphical illustrations are made for better justification of the model.


ORiON ◽  
2007 ◽  
Vol 23 (2) ◽  
Author(s):  
VSS Yadavalli ◽  
B Sivakumar ◽  
G Arivarignan

Author(s):  
Giuseppe Bernabei ◽  
Francesco Costantino ◽  
Laura Palagi ◽  
Riccardo Patriarca ◽  
Francesco Romito

Spare parts management affects significantly costs and service level for supply chains. This paper deals with an inventory management problem for multi-item repairable systems via a systemic perspective based on a new efficient integer black-box optimization model. With respect to the traditionally used marginal allocation that considers items individually, the proposed black-box optimization model is a holistic approach in the fact that it exploits relationships among items. The authors propose a derivative-free algorithm specifically tied to the application which exploits a new selection strategy for choosing entire subsets of items with the aim to get the best expected improvement in the objective function. The approach has been tested on a real case study for optimizing stocks in an airline's inventory network. The case study provides evidence about the good behavior of the exploratory geometry of the proposed approach in finding quickly a feasible and optimal solution for inventory control.


2020 ◽  
Vol 66 (6) ◽  
pp. 2628-2652 ◽  
Author(s):  
Bharadwaj Kadiyala ◽  
Özalp Özer ◽  
Alain Bensoussan

This paper studies an inventory management problem faced by an upstream supplier that is in a collaborative agreement, such as vendor-managed inventory (VMI), with a retailer. A VMI partnership provides the supplier an opportunity to manage inventory for the supply chain in exchange for point-of-sales (POS)- and inventory-level information from the retailer. However, retailers typically possess superior local market information and as has been the case in recent years, are able to capture and analyze customer purchasing behavior beyond the traditional POS data. Such analyses provide the retailer access to market signals that are otherwise hard to capture using POS information. We show and quantify the implication of the financial obligations of each party in VMI that renders communication of such important market signals as noncredible. To help institute a sound VMI collaboration, we propose learn and screen—a dynamic inventory mechanism—for the supplier to effectively manage inventory and information in the supply chain. The proposed mechanism combines the ability of the supplier to learn about market conditions from POS data (over multiple selling periods) and dynamically determine when to screen the retailer and acquire his private demand information. Inventory decisions in the proposed mechanism serve a strategic purpose in addition to their classic role of satisfying customer demand. We show that our proposed dynamic mechanism significantly improves the supplier’s expected profit and increases the efficiency of the overall supply chain operations under a VMI agreement. In addition, we determine the market conditions in which a strategic approach to VMI results in significant profit improvements for both firms, particularly when the retailer has high market power (i.e., when the supplier highly depends on the retailer) and when the supplier has relatively less knowledge about the end customer/market compared with the retailer. This paper was accepted by Gad Allon, operations management.


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