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Author: Yahong Zheng
Publisher:
ISBN:
Category :
Languages : en
Pages : 200
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Book Description
Supply chain management involves a wide range of activities. Among most of them, uncertainty exists inherently and always brings some consequence not expected. However, uncertainty is not considered much in conventional supply chain management. In the case where availability of resources is not what we expect, complexity of supply chain management increases. Taking constraints of uncertainty and availability into account, we aim to discuss supply chain management from different aspects. This thesis is an attempt of systematic and complete research from this point and we would like to offer some references to researchers and managers in supply chain. We focus on three classic sources of uncertainty: demand, manufacturing and distribution. For each source of uncertainty, we analyze its cause and its impact to the performance of the supply chain. Uncertainty is specified into concrete classic problem and an approach is proposed to solve it. Furthermore, bi-level newsboy problem as a miniature of supply chain, is focused under double uncertain environment. Treating uncertain variables is actually a treatment on operational level. The methods used offer good demonstration in treating uncertain variables in decision problems.
Author: Yahong Zheng
Publisher:
ISBN:
Category :
Languages : en
Pages : 200
Get Book Here
Book Description
Supply chain management involves a wide range of activities. Among most of them, uncertainty exists inherently and always brings some consequence not expected. However, uncertainty is not considered much in conventional supply chain management. In the case where availability of resources is not what we expect, complexity of supply chain management increases. Taking constraints of uncertainty and availability into account, we aim to discuss supply chain management from different aspects. This thesis is an attempt of systematic and complete research from this point and we would like to offer some references to researchers and managers in supply chain. We focus on three classic sources of uncertainty: demand, manufacturing and distribution. For each source of uncertainty, we analyze its cause and its impact to the performance of the supply chain. Uncertainty is specified into concrete classic problem and an approach is proposed to solve it. Furthermore, bi-level newsboy problem as a miniature of supply chain, is focused under double uncertain environment. Treating uncertain variables is actually a treatment on operational level. The methods used offer good demonstration in treating uncertain variables in decision problems.
Author: Tsan-Ming Choi
Publisher: Springer Science & Business Media
ISBN: 3642192572
Category : Business & Economics
Languages : en
Pages : 651
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Book Description
Channel coordination is a core subject of supply chain management. Over the past decade, much research effort has been devoted to exploring the detailed mechanisms for achieving supply chain coordination under uncertainty, generating many fruitful analytical and empirical results. Despite the abundance of research results, there is an absence of a comprehensive reference source that provides state-of-the-art findings on both theoretical and applied research on the subject. In addition, with the advance of knowledge and technologies, many new topics on supply chain coordination under uncertainty have appeared in recent years. This handbook extensively examines supply chain coordination challenges with a focal point on discovering innovative measures that can help tackle the existing and emerging challenges. The book is organized into five parts, which include chapters on innovative analytical models for coordination, channel power and bargaining, technological advancements and applications, empirical analysis, cases studies and review. This handbook provides new empirical and analytical results with precious insights, which will not only help supply chain agents to understand more about the latest measures for supply chain coordination under uncertainty, but also help practitioners and researchers to know how to improve supply chain performance based on innovative methods.
Author: Juping Shao
Publisher: Springer
ISBN: 3662472503
Category : Business & Economics
Languages : en
Pages : 197
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Book Description
The subject of this book is supply chain logistics planning optimization under multiple uncertainties, the key issue in supply chain management. Focusing on the strategic-alliance three-level supply chain, the model of supply chain logistics planning was established in terms of the market prices and the market requirements as random variables of manufactured goods with random expected value programming theory, and the hybrid intelligence algorithm solution model was designed. Aiming at the decentralized control supply chain, in which the nodes were unlimited expansion, the chance-constrained stochastic programming model was created in order to obtain optimal decision-making at a certain confidence level. In addition, the hybrid intelligence algorithm model was designed to solve the problem of supply chain logistics planning with the prices of the raw-materials supply market of the upstream enterprises and the prices of market demand for products of the downstream enterprises as random variables in the supply chain unit. Aimed at the three-stage mixed control supply chain, a logistics planning model was designed using fuzzy random programming theory with customer demand as fuzzy random variables and a hybrid intelligence algorithm solution was created. The research has significance both in theory and practice. Its theoretical significance is that the research can complement and perfect existing supply chain planning in terms of quantification. Its practical significance is that the results will guide companies in supply chain logistics planning in the uncertain environment.
Author: Dmitry Ivanov
Publisher: Springer Science & Business Media
ISBN: 1848829523
Category : Technology & Engineering
Languages : en
Pages : 286
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Book Description
Adaptive Supply Chain Management develops new viewpoints on the SCM goal paradigm, problem semantics, and decision-making support. Drawing upon years of research and practical experience, and using numerous examples, the authors unite conceptual considerations of supply chains with a constructive level of engineering and solutions to real-world problems. Adaptive Supply Chain Management provides advanced insights into dynamics, complexity, and uncertainty in supply chains from the perspectives of systems analysis, control theory, and operations research. It also considers supply chain adaptability, stability, and crisis-resistance. Providing readers with a comprehensive view of advanced SCM concepts, constructive mathematical techniques and models, Adaptive Supply Chain Management is an invaluable text for practitioners and researchers who specialize in SCM and operations.
Author: Lawrence V. Snyder
Publisher: John Wiley & Sons
ISBN: 1119024846
Category : Business & Economics
Languages : en
Pages : 784
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Book Description
Comprehensively teaches the fundamentals of supply chain theory This book presents the methodology and foundations of supply chain management and also demonstrates how recent developments build upon classic models. The authors focus on strategic, tactical, and operational aspects of supply chain management and cover a broad range of topics from forecasting, inventory management, and facility location to transportation, process flexibility, and auctions. Key mathematical models for optimizing the design, operation, and evaluation of supply chains are presented as well as models currently emerging from the research frontier. Fundamentals of Supply Chain Theory, Second Edition contains new chapters on transportation (traveling salesman and vehicle routing problems), integrated supply chain models, and applications of supply chain theory. New sections have also been added throughout, on topics including machine learning models for forecasting, conic optimization for facility location, a multi-supplier model for supply uncertainty, and a game-theoretic analysis of auctions. The second edition also contains case studies for each chapter that illustrate the real-world implementation of the models presented. This edition also contains nearly 200 new homework problems, over 60 new worked examples, and over 140 new illustrative figures. Plentiful teaching supplements are available, including an Instructor’s Manual and PowerPoint slides, as well as MATLAB programming assignments that require students to code algorithms in an effort to provide a deeper understanding of the material. Ideal as a textbook for upper-undergraduate and graduate-level courses in supply chain management in engineering and business schools, Fundamentals of Supply Chain Theory, Second Edition will also appeal to anyone interested in quantitative approaches for studying supply chains.
Author: Joseph Geunes
Publisher: Springer Science & Business Media
ISBN: 0387262814
Category : Business & Economics
Languages : en
Pages : 418
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Book Description
Supply Chain Optimization captures the latest results in a segment of current research activity in supply chain management. This research area focuses on applying optimization techniques to supply chain management problems. The research papers that make up the volume provide a snapshot of state-of-the-art optimization methods within the field. This book presents rigorous modelling approaches for supply chain operations problems with a goal of improving supply chain performance (or the performance of some segment thereof). It contains high-quality works from leading researchers in the field whose expertise fits within this scope. The book provides a diverse blend of research topics and novel modelling and solution approaches for difficult classes of supply chain operations, planning, and design problems.
Author: Hosang Jung
Publisher: Springer Science & Business Media
ISBN: 1846286077
Category : Business & Economics
Languages : en
Pages : 453
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Book Description
This edited book describes new trends in supply chain design and management with an emphasis on technologies and methodologies. It contains guidelines detailing the real-world applications of these technologies and methodologies. This book is of interest to researchers and practitioners and can also be used as a reference handbook by lecturers and postgraduate students in this field.
Author: Thorsten Blecker
Publisher: Erich Schmidt Verlag GmbH & Co KG
ISBN: 9783503097371
Category : Business logistics
Languages : en
Pages : 364
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Book Description
Supply chains are faced with a rising complexity with manifold effects. Because of the strong link between a supply chain's complexity and its efficiency, supply chain complexity management becomes a major challenge of today's business management. Therefore logistics and the supply chain management can play a significant role in mastering and managing complexity. The new book, edited by Thorsten Blecker and Wolfgang Kersten, is exemplifying the current progress in complexity management. Separate chapters are dedicated to clarify complexity management in transportation, networks and supply chains. It offers important insights of global and flexible network modelling to manage complexity, complexity in supply chains - developing human resource strategy, performance measurement of green supply chain management, complexity in transportation by means of containers and air-cargos. The volume, written by well-known experts of supply chain management from all over the world, shows applicable solutions, practical examples and use cases to illustrate complexity management and its application in logistics and supply chain management. It presents the central perspectives for a modern complexity management in supply chains. Therefore the book offers a fundamental understanding for workable complexity management concept their implementation to practitioners. The book offers fundamental insights into actual problems of an general complexity management concept and their implementation to practitioners in industry, logistics, management, service sector, research and apprenticeship. In addition to this it gives a valuable insight to the status of complexity management also for lecturers and students.
Author: Haresh Gurnani
Publisher: Springer Science & Business Media
ISBN: 0857297783
Category : Technology & Engineering
Languages : en
Pages : 339
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Book Description
One of the most critical issues facing supply chain managers in today’s globalized and highly uncertain business environments is how to deal proactively with disruptions that might affect the complicated supply networks characterizing modern enterprises. Supply Chain Disruptions: Theory and Practice of Managing Risk presents a state-of the-art perspective on this particular issue. Supply Chain Disruptions: Theory and Practice of Managing Risk demonstrates that effective management of supply disruptions necessitates both strategic and tactical measures – the former involving optimal design of supply networks; the latter involving inventory, finance and demand management. It shows that managers ought to use all available levers at their disposal throughout the supply network – like sourcing and pricing strategies, providing financial subsidies, encouraging information sharing and incentive alignment between supply chain partners – in order to tackle supply disruptions. The editors combine up-to-date academic research with the latest operational risk management practices used in industry to demonstrate how theoreticians and practitioners can learn from each other. As well as providing a wealth of knowledge for students and professors who are interested in pursuing research or teaching courses in the rapidly growing area of supply chain risk management, Supply Chain Disruptions: Theory and Practice of Managing Risk also acts as a ready reference for practitioners who are interested in understanding the theoretical underpinnings of effective supply disruption management techniques.
Author: Mengshi Lu
Publisher:
ISBN:
Category :
Languages : en
Pages : 97
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Book Description
Traditional supply chain management models typically require complete model information, including structural relationships (e.g., how pricing decisions affect customer demand), probabilistic distributions, and parameters. However, in practice, the model information may be uncertain. My dissertation research seeks to address model uncertainty in supply chain management problems using data-driven and robust methods. Incomplete information typically comes in two forms, namely, historical data and partial information. When historical data are available, data-driven methods can be used to obtain decisions directly from data, instead of estimating the model information and then using these estimates to find the optimal solution. When partial information is available, robust methods consider all possible scenarios and make decisions to hedge against the worst-case scenario effectively, instead of making simplified assumptions that could lead to significant loss. Chapter 1 provides an overview of model uncertainty in supply chain management, and discusses the limitations of the traditional methods. The main part of the dissertation is on the application of data-driven and robust methods to three widely-studied supply chain management problems with model uncertainty. Chapter 2 studies the reliable facility location problem where the joint-distribution of facility disruptions is uncertain. For this problem, usually, only partial information in the form of marginal facility disruption probabilities is available. Most existing models require the assumption that the disruptions at different locations are independent of each other. However, in practice, correlated disruptions are widely observed. We present a model that allows disruptions to be correlated with an uncertain joint distribution, and apply distributionally-robust optimization to minimize the expected cost under the worst-case distribution with the given marginal disruption probabilities. The worst-case distribution has a practical interpretation, and its sparse structure allows us to solve the problem efficiently. We find that ignoring disruption correlation could lead to significant loss. The robust method can significantly reduce the regret from model misspecification. It outperforms the traditional approach even under very mild correlation. Most of the benefit of the robust model can be captured at a relatively small cost, which makes it easy to implement in practice. Chapter 3 studies the pricing newsvendor problem where the structural relationship between pricing decisions and customer demand is unknown. Traditional methods for this problem require the selection of a parametric demand model and fitting the model using historical data, while model selection is usually a hard problem in itself. Furthermore, most of the existing literature on pricing requires certain conditions on the demand model, which may not be satisfied by the estimates from data. We present a data-driven approach based only on the historical observations and the basic domain knowledge. The conditional demand distribution is estimated using non-parametric quantile regression with shape constraints. The optimal pricing and inventory decisions are determined numerically using the estimated quantiles. Smoothing and kernelization methods are used to achieve regularization and enhance the performance of the approach. Additional domain knowledge, such as concavity of demand with respect to price, can also be easily incorporated into the approach. Numerical results show that the data-driven approach is able to find close-to-optimal solutions. Smoothing, kernelization, and the incorporation of additional domain knowledge can significantly improve the performance of the approach. Chapter 4 studies inventory management for perishable products where a parameter of the demand distribution is unknown. The traditional separated estimation-optimization approach for this problem has been shown to be suboptimal. To address this issue, an integrated approach called operational statistics has been proposed. We study several important properties of operational statistics. We find that the operational statistics approach is consistent and guaranteed to outperform the traditional approach. We also show that the benefit of using operational statistics is larger when the demand variability is higher. We then generalize the operational statistics approach to the risk-averse newsvendor problem under the conditional value-at-risk (CVaR) criterion. Previous results in operational statistics can be generalized to maximize the expectation of conditional CVaR. In order to model risk-aversion to both the uncertainty in demand sampling and the uncertainty in future demand, we introduce a new criterion called the total CVaR, and find the optimal operational statistic for this new criterion.
