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Author: Abdullah Yahia M. Alfaify
Publisher:
ISBN:
Category : University of Ottawa theses
Languages : en
Pages : 0
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Book Description
Optimizing supply chain is the most successful key for manufacturing systems to be competitive. Supply chain (SC) has gotten intensive research works at all levels: strategic, tactical, and operational levels. These levels, in some researches, have integrated with each other or integrated with other planning issues such as inventory. Optimizing inventory location and level of safety stock at all supply chain partners is essential in high competitive markets to manage uncertain demand and service level. Many works have been developed to optimize the location of safety stock along supply chain, which is important for fast response to fluctuation in demand. However, most of these studies focus on the design stage of a supply chain. Because demand at different horizon times may vary according to different reasons such as the entry of different competitors on market or seasonal demand, safety stock should be optimized accordingly. At the planning (tactical) level, safety stock can be controlled according to each planning horizon to satisfy customer demand at lower cost instead of being fixed by a decision taken at the strategic level. On the other hand, most studies that consider safety stock optimization are tied to a specific system structure such as serial, assembly, or distribution structure. This research focuses on formulating two different models. First, a multi- echelon safety stock optimization (MESSO) model for general supply chain topology is formulated. Then, it is converted into a robust form (RMESSO) which considers all possible fluctuation in demand and gives a solution that is valid under any circumstances. Second, the safety stock optimization model is integrated with tactical supply chain planning (SCP) for manufacturing systems. The integrated model is a multi-objective mixed integer non-linear programming (MINLP) model. This model aims to minimize the total cost and total time. A case study for each model is provided and the numerical results are analyzed.
Author: Abdullah Yahia M. Alfaify
Publisher:
ISBN:
Category : University of Ottawa theses
Languages : en
Pages : 0
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Book Description
Optimizing supply chain is the most successful key for manufacturing systems to be competitive. Supply chain (SC) has gotten intensive research works at all levels: strategic, tactical, and operational levels. These levels, in some researches, have integrated with each other or integrated with other planning issues such as inventory. Optimizing inventory location and level of safety stock at all supply chain partners is essential in high competitive markets to manage uncertain demand and service level. Many works have been developed to optimize the location of safety stock along supply chain, which is important for fast response to fluctuation in demand. However, most of these studies focus on the design stage of a supply chain. Because demand at different horizon times may vary according to different reasons such as the entry of different competitors on market or seasonal demand, safety stock should be optimized accordingly. At the planning (tactical) level, safety stock can be controlled according to each planning horizon to satisfy customer demand at lower cost instead of being fixed by a decision taken at the strategic level. On the other hand, most studies that consider safety stock optimization are tied to a specific system structure such as serial, assembly, or distribution structure. This research focuses on formulating two different models. First, a multi- echelon safety stock optimization (MESSO) model for general supply chain topology is formulated. Then, it is converted into a robust form (RMESSO) which considers all possible fluctuation in demand and gives a solution that is valid under any circumstances. Second, the safety stock optimization model is integrated with tactical supply chain planning (SCP) for manufacturing systems. The integrated model is a multi-objective mixed integer non-linear programming (MINLP) model. This model aims to minimize the total cost and total time. A case study for each model is provided and the numerical results are analyzed.
Author: Stefan Minner
Publisher: Springer Science & Business Media
ISBN: 3642582966
Category : Business & Economics
Languages : en
Pages : 221
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Book Description
Increasing customer requirements, product variety, and market competition demand for service and cost improvements by model based inventory control in supply chains. The book presents approaches for safety stock determination in manufacturing and logistics networks. Most of the existing literature provides methods for very specific types of supply networks. The approach presented in this book follows a material flow philosophy that allows for several extensions of the basic models and therefore offers a wide applicability within decision support systems. Models for several types of problems and network structures are presented and analyzed to develop efficient optimization algorithms and heuristics.
Author: Feng Tian
Publisher:
ISBN:
Category :
Languages : en
Pages : 232
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Book Description
Abstract: Advanced planning and scheduling (APS) has been implemented in major corporations for over twenty years. In comparison, multi-echelon inventory optimization systems (IOS) are still at an earlier point in their adoption cycle. The adoption of inventory optimization will create the opportunity to jointly solve the production and inventory problem, enabling planners to bring model-based results to a revised sales, inventory, and operations process. Traditionally, APS and IOS are considered belong to difference planning layers and are solved independently. APS systems are every day use operational planning tool, and generally assume deterministic demand and assign a linear penalty cost for both demand and inventory shortfalls. While resource capacity is always taken into consideration in APS systems, managing uncertainty is beyond its capability. On the other hand, IOS is taken as part of the tactical planning and has long been developed to treat the demand uncertainty. But current development always sacrifices some system complexity, such as capacity constraint. Hierarchical decision making and monolithic model are the two approaches exist to solve the production-inventory problems. However, the hierarchical approach does not guarantee the solution of top-level aggregate model can generate a feasible disaggregation for the item-level problem. Most of current monolithic models still lack the capability to handle the safety stock issue in a general planning system. This research formulates the integrated production-inventory problem faced in a semiconductor supply chain. The emphasis of our work is on finding practical solutions to support planners making production and inventory decisions as part of their operation planning process. Our work will start with iteratively solving two known optimization problems: a production planning optimization and a multi-echelon inventory optimization. While this iterative approach can admittedly produce a suboptimal solution, it represents a good start to understand the correlation of the inventory optimization problem and the production planning problem. Then we will work on an integrated model that optimizes inventory and production planning problems simultaneously. While the problem context is one major semiconductor manufacturer, and semiconductor manufacturing does have domain-specific nuances, our resulting formulation is general enough to apply to any discrete-parts manufacturing operation.
Author: J. George Shanthikumar
Publisher: Springer Science & Business Media
ISBN: 1461503736
Category : Business & Economics
Languages : en
Pages : 413
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Book Description
This volume originates from two workshops, both focusing on themes that are reflected in the title of the volume. The first workshop took place at Eindhoven University of Technology, April 24-26, 2001, on the occasion of the University granting a doctorate honoris causa to Profes sor John A. Buzacott. The second workshop was held on June 15, 2002 at Cornell University (preceding the annual INFORMSjMSOM Confer ence), honoring John's retirement and his lifetime contributions. Each of the two workshops consisted of about a dozen technical presentations. The objective of the volume, however, is not to simply publish the proceedings of the two workshops. Rather, our objective is to put to gether a select set of articles, each organized into a well-written chapter, focusing on a timely topic. Collected into a single volume, these chapters aim to serve as a useful reference for researchers and practitioners alike, and also as reading materials for graduate courses or seminars.
Author: Nicolas Vandeput
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110673940
Category : Business & Economics
Languages : en
Pages : 318
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Book Description
In this book . . . Nicolas Vandeput hacks his way through the maze of quantitative supply chain optimizations. This book illustrates how the quantitative optimization of 21st century supply chains should be crafted and executed. . . . Vandeput is at the forefront of a new and better way of doing supply chains, and thanks to a richly illustrated book, where every single situation gets its own illustrating code snippet, so could you. --Joannes Vermorel, CEO, Lokad Inventory Optimization argues that mathematical inventory models can only take us so far with supply chain management. In order to optimize inventory policies, we have to use probabilistic simulations. The book explains how to implement these models and simulations step-by-step, starting from simple deterministic ones to complex multi-echelon optimization. The first two parts of the book discuss classical mathematical models, their limitations and assumptions, and a quick but effective introduction to Python is provided. Part 3 contains more advanced models that will allow you to optimize your profits, estimate your lost sales and use advanced demand distributions. It also provides an explanation of how you can optimize a multi-echelon supply chain based on a simple—yet powerful—framework. Part 4 discusses inventory optimization thanks to simulations under custom discrete demand probability functions. Inventory managers, demand planners and academics interested in gaining cost-effective solutions will benefit from the "do-it-yourself" examples and Python programs included in each chapter.
Author: Sridhar Tayur
Publisher: Springer Science & Business Media
ISBN: 9780792383444
Category : Business & Economics
Languages : en
Pages : 898
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Book Description
Quantitative models and computer-based tools are essential for making decisions in today's business environment. These tools are of particular importance in the rapidly growing area of supply chain management. This volume is a unified effort to provide a systematic summary of the large variety of new issues being considered, the new set of models being developed, the new techniques for analysis, and the computational methods that have become available recently. The volume's objective is to provide a self-contained, sophisticated research summary - a snapshot at this point of time - in the area of Quantitative Models for Supply Chain Management. While there are some multi-disciplinary aspects of supply chain management not covered here, the Editors and their contributors have captured many important developments in this rapidly expanding field. The 26 chapters can be divided into six categories. Basic Concepts and Technical Material (Chapters 1-6). The chapters in this category focus on introducing basic concepts, providing mathematical background and validating algorithmic tools to solve operational problems in supply chains. Supply Contracts (Chapters 7-10). In this category, the primary focus is on design and evaluation of supply contracts between independent agents in the supply chain. Value of Information (Chapters 11-13). The chapters in this category explicitly model the effect of information on decision-making and on supply chain performance. Managing Product Variety (Chapters 16-19). The chapters in this category analyze the effects of product variety and the different strategies to manage it. International Operations (Chapters 20-22). The three chapters in this category provide an overview of research in the emerging area of International Operations. Conceptual Issues and New Challenges (Chapters 23-27). These chapters outline a variety of frameworks that can be explored and used in future research efforts. This volume can serve as a graduate text, as a reference for researchers and as a guide for further development of this field.
Author: Peng Li
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
Author: Adolfo Crespo Márquez
Publisher: Springer Science & Business Media
ISBN: 1848826818
Category : Technology & Engineering
Languages : en
Pages : 297
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Book Description
"Dynamic Modelling for Supply Chain Management" discusses how to streamline complex supply chain management by making the most of the growing number of tools available. The reader is introduced to the basic foundations from which to develop intelligent management strategies, as the book characterises the process and framework of modern supply chain management. The author reviews supply chain management concepts and singles out important factors in the management of modern complex production systems. Particular attention is paid to modern simulation modelling tools that can be used to support supply chain planning and control. The book explores the operational and financial impacts of various potential problems, offering a compilation of practical models to help identify solutions. A useful reference on supply chain management, "Dynamic Modelling for Supply Chain Management" will benefit engineers and professionals working in a variety of areas, from supply chain management to product engineering.
Author: Yu Hua (M. Eng.)
Publisher:
ISBN:
Category :
Languages : en
Pages : 86
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Book Description
This work illustrates how to apply a multi-echelon periodic review base-stock model to a real manufacturing company, Waters Corporation, for their major product Analytical Columns. At Waters, the Analytical Column supply chain ranges from raw materials to the final delivery to customers, and covers US, Europe, and Asia. The goal of this work is to find the best locations to hold safety stock along the supply chain so as to minimize the inventory holding cost for the whole company. To do this analysis, a 5 stage multi-echelon supply chain model is constructed. All the stage costs are measured and standardized based on data from the "SAP" system. To estimate the demand variability, we utilize an adjustment method that accounts for the aggregate bias in the forecast. The final optimal solution will reduce the safety stock level by 67% for the supply chain. We also find a nearoptimal solution that is easier to implement; this solution would reduce the safety stocks by 59%. Finally, we argue that the implementation of this model and its assumed operating policies can improve internal communications within the company, leading to better integration across operating units..
Author: Stefan Voß
Publisher: Springer Science & Business Media
ISBN: 3540247645
Category : Business & Economics
Languages : en
Pages : 239
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Book Description
An easy-to-read introduction to the concepts associated with the creation of optimization models for production planning starts off this book. These concepts are then applied to well-known planning models, namely mrp and MRP II. From this foundation, fairly sophisticated models for supply chain management are developed. Another unique feature is that models are developed with an eye toward implementation. In fact, there is a chapter that provides explicit examples of implementation of the basic models using a variety of popular, commercially available modeling languages.
