A Study of Multi-echelon Inventory Systems with Sochastic Capacity and Intermediate Product Demand
A Study of Multi-echelon Inventory Systems with Sochastic Capacity and Intermediate Product Demand

Author: Suman Nirajan

Publisher:

Published: 2008

Total Pages: 319

ISBN-13:

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The research in this dissertation involves the study of several multi-echelon inventory systems with stochastic capacity and intermediate product demand. Specifically we analyze the behavior of the system which consists of several intermediate product demands. The analysis is primarily three fold i) developed update (relational) equations for all the multi-echelon inventory systems under several inventory allocation policies, ii) develop two simulation optimization approaches 1) OptQuest framework, and 2) IPA (Infinitesimal Perturbation Analysis) framework, used to minimize the total cost of the inventory systems that satisfy the desired customer service level, iii) obtain numerical results for all the multi-echelon inventory systems under several scenarios and instances, and an extensive analysis and implications of the results. The research done in this dissertation differ from earlier works, since it considers a complex (combination of serial and assembly systems) multi-period multi-echelon inventory system with several sources of demand (specifically intermediate product demands). We obtain the best found base-stock levels for each node in the system that satisfies the required customer service level. A SIO (Simulation based Inventory Optimization) approach is used to obtain the best found base-stock level for the system under several inventory allocation policies. We consider a system which is closer to the actual world and can be used to solve contemporary issues like, 1) manufacturing firm that produces finished products as well as spare parts, 2) manufacturer-warehouse-distribution center-retail outlets etc. I am not aware of any work that studies the impact of inventory allocation polices for multi-period in a multi-echelon inventory system, and obtains best found base stock level for each node using an IPA framework. Moreover the best found base-stock level for each node is obtained under realistic conditions like stochastic demand, stochastic capacity, and lead time.

Continuous-Review Policies for a Multi-Echelon Inventory Problem with Stochastic Demand (Classic Reprint)
Continuous-Review Policies for a Multi-Echelon Inventory Problem with Stochastic Demand (Classic Reprint)

Author: Marc De Bodt

Publisher: Forgotten Books

Published: 2017-10-19

Total Pages: 56

ISBN-13: 9780265499399

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Excerpt from Continuous-Review Policies for a Multi-Echelon Inventory Problem With Stochastic Demand Most multi - echelon inventory systems have significant stochastic characteristics. Yet most of the inventory control systems in practice, such as materials requirements planning (mrp) systems, either ignore these stochastic elements or deal with them intnloverly simplistic manner. Furthermore in the inventory literature there is very little theory that can be applied to these problems. In this paper we hope to make a small step at improving this theory. We consider a simple multi - echelon system, namely a serial system, for which we determine continuous - review control policies. We base this analysis on an approximate cost model that is a direct extension to the approximate cost model used for a single - item, continuous - review inventory problem. The resulting solution is quite analogous to that for the single - item model, that being the determination_ of a reorder point and a reorder quantity. In the remainder of this section we give a brief review of some relevant literature. About the Publisher Forgotten Books publishes hundreds of thousands of rare and classic books. Find more at www.forgottenbooks.com This book is a reproduction of an important historical work. Forgotten Books uses state-of-the-art technology to digitally reconstruct the work, preserving the original format whilst repairing imperfections present in the aged copy. In rare cases, an imperfection in the original, such as a blemish or missing page, may be replicated in our edition. We do, however, repair the vast majority of imperfections successfully; any imperfections that remain are intentionally left to preserve the state of such historical works.

Continuous-Review Policies for a Multi-Echelon Inventory Problem with Stochastic Demand
Continuous-Review Policies for a Multi-Echelon Inventory Problem with Stochastic Demand

Author: Marc De Bodt

Publisher: Palala Press

Published: 2015-09-05

Total Pages: 60

ISBN-13: 9781341603174

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This work has been selected by scholars as being culturally important, and is part of the knowledge base of civilization as we know it. This work was reproduced from the original artifact, and remains as true to the original work as possible. Therefore, you will see the original copyright references, library stamps (as most of these works have been housed in our most important libraries around the world), and other notations in the work. This work is in the public domain in the United States of America, and possibly other nations. Within the United States, you may freely copy and distribute this work, as no entity (individual or corporate) has a copyright on the body of the work.As a reproduction of a historical artifact, this work may contain missing or blurred pages, poor pictures, errant marks, etc. Scholars believe, and we concur, that this work is important enough to be preserved, reproduced, and made generally available to the public. We appreciate your support of the preservation process, and thank you for being an important part of keeping this knowledge alive and relevant.

The Design of Multi-Product Multi-Echelon Inventory Systems Using a Branch-and-Bound Algorithm
The Design of Multi-Product Multi-Echelon Inventory Systems Using a Branch-and-Bound Algorithm

Author: Charles Edward Pinkus

Publisher:

Published: 1971

Total Pages: 151

ISBN-13:

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Large-scale distribution systems require a hierarchy of retail stores and warehouses to satisfy the demand of their customers. Given the maximum number of installations and their possible locations, the problem is to determine which installations to include in the design of the system and which products to stock at these installations. Demand for the products is assumed known and may be deterministic or stochastic. The objective is to find a solution to this design problem which minimizes the total (expected) discounted cost for the lifetime of the system. This problem has been formulated as a combinatorial optimization problem and solved by a branch-and-bound algorithm. The subproblems of the algorithm are tractable integer linear programs. Applications of this model to the design of other multi-use, multi-facility systems are briefly described. (Author).

Effective Multi-echelon Inventory Systems for Supplier Selection and Order Allocation
Effective Multi-echelon Inventory Systems for Supplier Selection and Order Allocation

Author: Cong Guo (Industrial engineer)

Publisher:

Published: 2014

Total Pages: 131

ISBN-13:

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Successful supply chain management requires an effective sourcing strategy to counteract uncertainties in both the suppliers and demands. Therefore, determining a better sourcing policy is critical in most of industries. Supplier selection is an essential task within the sourcing strategy. A well-selected set of suppliers makes a strategic difference to an organization's ability to reduce costs and improve the quality of its end products. To discover the cost structure of selecting a supplier, it is more interesting to further determine appropriate levels of inventory in each echelon for different suppliers. This dissertation focuses on the study of the integrated supplier selection, order allocation and inventory control problems in a multi-echelon supply chain. First, we investigate a non-order-splitting inventory system in supply chain management. In particular, a buyer firm that consists of one warehouse and N identical retailers procures a type of product from a group of potential suppliers, which may have different prices, ordering costs, lead times and have restriction on minimum and maximum total order size, to satisfy stochastic demand. A continuous review system that implements the order quantity, reorder point (Q, R) inventory policy is considered in the proposed model. The model is solved by decomposing the mixed integer nonlinear programming model into two sub-models. Numerical experiments are conducted to evaluate the model and some managerial insights are obtained with sensitivity analysis. In the next place, we extend the study to consider the multi-echelon system with the order-splitting policy. In particular, the warehouse acquisition takes place when the inventory level depletes to a reorder point R, and the order Q is simultaneously split among m selected suppliers. This consideration is important since it could pool lead time risks by splitting replenishment orders among multiple suppliers simultaneously. We develop an exact analysis for the order-splitting model in the multi-echelon system, and formulate the problem in a Mixed Integer Nonlinear Programming (MINLP) model. To demonstrate the solvability and the effectiveness of the model, we conduct several numerical analyses, and further conduct simulation models to verify the correctness of the proposed mathematical model.

Optimal Design of Multi-Product Multi-Echelon Inventory Systems
Optimal Design of Multi-Product Multi-Echelon Inventory Systems

Author: Charles E. Pinkus

Publisher:

Published: 1972

Total Pages: 33

ISBN-13:

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Large scale inventory distribution system typically comprise a hierarchy of retail stores and warehouses. The paper presents a model for finding the optimal design of such systems. Given the maximum number of facilities under consideration and their possible locations, the problem is to determine which facilities to include in the system and which products to stock at each in order to minimize the cost of the system. Demand for the products may be deterministic or stochastic. To use the model it is necessary to know the optimal inventory policies for the multi-echelon systems under consideration, however, an important feature of this work is that any multi-echelon model may be used in tandem with this design model. Included is an example to illustrate the model and the two points which are the basis for its formulation: first, there is generally no single design which is best for all products; second, the design which is optimal for a given product is not necessarily the best design to use when trying to minimize the cost of the entire system. (Author).

Introduction to Distribution Logistics
Introduction to Distribution Logistics

Author: Paolo Brandimarte

Publisher: John Wiley & Sons

Published: 2007-07-27

Total Pages: 608

ISBN-13: 0470170042

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unique introduction to distribution logistics that focuses on both quantitative modeling and practical business issues Introduction to Distribution Logistics presents a complete and balanced treatment of distribution logistics by covering both applications and the required theoretical background, therefore extending its reach to practitioners and students in a range of disciplines such as management, engineering, mathematics, and statistics. The authors emphasize the variety and complexity of issues and sub-problems surrounding distribution logistics as well as the limitations and scope of applicability of the proposed quantitative tools. Throughout the book, readers are provided with the quantitative approaches needed to handle real-life management problems, and areas of study include: Supply chain management Network design and transportation Demand forecasting Inventory control in single- and multi-echelon systems Incentives in the supply chain Vehicle routing Complete with extensive appendices on probability and statistics as well as mathematical programming, Introduction to Distribution Logistics is a valuable text for distribution logistics courses at both the advanced undergraduate and beginning graduate levels in a variety of disciplines, and prior knowledge of production planning is not assumed. The book also serves as a useful reference for practitioners in the fields of applied mathematics and statistics, manufacturing engineering, business management, and operations research. The book's related Web site includes additional sections and numerical illustrations.