Analysis and Algorithms for Service Parts Supply Chains PDF Download
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Author: John A. Muckstadt
Publisher: Springer Science & Business Media
ISBN: 0387272887
Category : Business & Economics
Languages : en
Pages : 290
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Book Description
* Provides a broad overview of modeling approaches and solution methodologies for addressing inventory problems, particularly the management of high cost, low demand rate service parts found in multi-echelon settings * The text may be used in a variety of courses for first-year graduate students or senior undergraduates, or as a reference for researchers and practitioners * A background in stochastic processes and optimization is assumed
Author: John A. Muckstadt
Publisher: Springer Science & Business Media
ISBN: 0387272887
Category : Business & Economics
Languages : en
Pages : 290
Get Book Here
Book Description
* Provides a broad overview of modeling approaches and solution methodologies for addressing inventory problems, particularly the management of high cost, low demand rate service parts found in multi-echelon settings * The text may be used in a variety of courses for first-year graduate students or senior undergraduates, or as a reference for researchers and practitioners * A background in stochastic processes and optimization is assumed
Author: Geert-Jan van Houtum
Publisher: Springer
ISBN: 1489976094
Category : Business & Economics
Languages : en
Pages : 227
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Book Description
This book focuses on the tactical planning level for spare parts management. It describes a series of multi-item inventory models and presents exact and heuristic optimization methods, including greedy heuristics that work well for real, life-sized problems. The intended audience consists of graduate students, starting scholars in the field of spare parts inventory control, and spare parts planning specialists in the industry. In individual chapters the authors consider topics including: a basic single-location model; single-location models with multiple machine types and/or machine groups; the multi-location model with lateral transshipments; the classical METRIC model and its generalization to multi-indenture systems; and a single-location model with an explicit modeling of the repair capacity for failed parts and the priorities that one can set there. Various chapters of the book are used in a master course at Eindhoven University of Technology and in a PhD course of the Graduate Program Operations Management and Logistics (a Dutch network that organizes PhD courses in the field of OM&L). The required pre-knowledge consists of probability theory and basic knowledge of Markov processes and queuing theory. End-of-chapter problems appear for all chapters, with some answers appearing in an appendix.
Author: Mahdi Fathi
Publisher: Springer Nature
ISBN: 3030285650
Category : Mathematics
Languages : en
Pages : 333
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Book Description
This volume provides resourceful thinking and insightful management solutions to the many challenges that decision makers face in their predictions, preparations, and implementations of the key elements that our societies and industries need to take as they move toward digitalization and smartness. The discussions within the book aim to uncover the sources of large-scale problems in socio-industrial dilemmas, and the theories that can support these challenges. How theories might also transition to real applications is another question that this book aims to uncover. In answer to the viewpoints expressed by several practitioners and academicians, this book aims to provide both a learning platform which spotlights open questions with related case studies. The relationship between Industry 4.0 and Society 5.0 provides the basis for the expert contributions in this book, highlighting the uses of analytical methods such as mathematical optimization, heuristic methods, decomposition methods, stochastic optimization, and more. The book will prove useful to researchers, students, and engineers in different domains who encounter large scale optimization problems and will encourage them to undertake research in this timely and practical field. The book splits into two parts. The first part covers a general perspective and challenges in a smart society and in industry. The second part covers several case studies and solutions from the operations research perspective for large scale challenges specific to various industry and society related phenomena.
Author: Larry B. Rainey
Publisher: John Wiley & Sons
ISBN: 1118460316
Category : Mathematics
Languages : en
Pages : 638
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Book Description
“...a much-needed handbook with contributions from well-chosen practitioners. A primary accomplishment is to provide guidance for those involved in modeling and simulation in support of Systems of Systems development, more particularly guidance that draws on well-conceived academic research to define concepts and terms, that identifies primary challenges for developers, and that suggests fruitful approaches grounded in theory and successful examples.” Paul Davis, The RAND Corporation Modeling and Simulation Support for System of Systems Engineering Applications provides a comprehensive overview of the underlying theory, methods, and solutions in modeling and simulation support for system of systems engineering. Highlighting plentiful multidisciplinary applications of modeling and simulation, the book uniquely addresses the criteria and challenges found within the field. Beginning with a foundation of concepts, terms, and categories, a theoretical and generalized approach to system of systems engineering is introduced, and real-world applications via case studies and examples are presented. A unified approach is maintained in an effort to understand the complexity of a single system as well as the context among other proximate systems. In addition, the book features: Cutting edge coverage of modeling and simulation within the field of system of systems, including transportation, system health management, space mission analysis, systems engineering methodology, and energy State-of-the-art advances within multiple domains to instantiate theoretic insights, applicable methods, and lessons learned from real-world applications of modeling and simulation The challenges of system of systems engineering using a systematic and holistic approach Key concepts, terms, and activities to provide a comprehensive, unified, and concise representation of the field A collection of chapters written by over 40 recognized international experts from academia, government, and industry A research agenda derived from the contribution of experts that guides scholars and researchers towards open questions Modeling and Simulation Support for System of Systems Engineering Applications is an ideal reference and resource for academics and practitioners in operations research, engineering, statistics, mathematics, modeling and simulation, and computer science. The book is also an excellent course book for graduate and PhD-level courses in modeling and simulation, engineering, and computer science.
Author: Wai-Ki Ching
Publisher: Springer Science & Business Media
ISBN: 1461463122
Category : Business & Economics
Languages : en
Pages : 259
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Book Description
This new edition of Markov Chains: Models, Algorithms and Applications has been completely reformatted as a text, complete with end-of-chapter exercises, a new focus on management science, new applications of the models, and new examples with applications in financial risk management and modeling of financial data. This book consists of eight chapters. Chapter 1 gives a brief introduction to the classical theory on both discrete and continuous time Markov chains. The relationship between Markov chains of finite states and matrix theory will also be highlighted. Some classical iterative methods for solving linear systems will be introduced for finding the stationary distribution of a Markov chain. The chapter then covers the basic theories and algorithms for hidden Markov models (HMMs) and Markov decision processes (MDPs). Chapter 2 discusses the applications of continuous time Markov chains to model queueing systems and discrete time Markov chain for computing the PageRank, the ranking of websites on the Internet. Chapter 3 studies Markovian models for manufacturing and re-manufacturing systems and presents closed form solutions and fast numerical algorithms for solving the captured systems. In Chapter 4, the authors present a simple hidden Markov model (HMM) with fast numerical algorithms for estimating the model parameters. An application of the HMM for customer classification is also presented. Chapter 5 discusses Markov decision processes for customer lifetime values. Customer Lifetime Values (CLV) is an important concept and quantity in marketing management. The authors present an approach based on Markov decision processes for the calculation of CLV using real data. Chapter 6 considers higher-order Markov chain models, particularly a class of parsimonious higher-order Markov chain models. Efficient estimation methods for model parameters based on linear programming are presented. Contemporary research results on applications to demand predictions, inventory control and financial risk measurement are also presented. In Chapter 7, a class of parsimonious multivariate Markov models is introduced. Again, efficient estimation methods based on linear programming are presented. Applications to demand predictions, inventory control policy and modeling credit ratings data are discussed. Finally, Chapter 8 re-visits hidden Markov models, and the authors present a new class of hidden Markov models with efficient algorithms for estimating the model parameters. Applications to modeling interest rates, credit ratings and default data are discussed. This book is aimed at senior undergraduate students, postgraduate students, professionals, practitioners, and researchers in applied mathematics, computational science, operational research, management science and finance, who are interested in the formulation and computation of queueing networks, Markov chain models and related topics. Readers are expected to have some basic knowledge of probability theory, Markov processes and matrix theory.
Author: Serguei Netessine
Publisher: Pearson Education
ISBN: 0137015070
Category : Business & Economics
Languages : en
Pages : 42
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Book Description
As manufacturing supply chains have moved from vertically integrated factories to diffused networks, manufacturers need to manage complex, global webs of suppliers. In this chapter, Netessine examines supply networks in two industries in particular: automobiles, and aerospace and defense. He explores how different strategies and technologies have helped companies manage, organize, and capitalize on their networks of suppliers. He discusses how Japanese automakers have used partnerships to outperform their U.S. rivals, who have taken a more adversarial approach to their suppliers. He also considers how companies such as Airbus and Boeing have used technology to coordinate and integrate far-flung networks. While Netessine notes that the formal study of network-based supply chains is just emerging, he offers insights from research and practice on the growing importance of supply networks and strategies for managing them successfully.
Author: Michael Freitag
Publisher: Springer Nature
ISBN: 3031053591
Category : Technology & Engineering
Languages : en
Pages : 502
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Book Description
Since 2007, the biennial International Conferences on Dynamics in Logistics (LDIC) offers researchersand practitioners from logistics, operations research, production, industrial and electrical engineering aswell as from computer science an opportunity to meet and to discuss the latest developments in thisparticular research domain. From February 23th to 25th 2022 for the eighth time, LDIC 2022 was held inBremen, Germany. Similar to its seven predecessors, the Bremen Research Cluster for Dynamics inLogistics (LogDynamics) organized this conference. The spectrum of topics reaches from the dynamicmodeling, planning and control of processes over supply chain management and maritime logistics toinnovative technologies and robotic applications for cyber-physical production and logistics systems.LDIC 2022 provided a forum for the discussion of advances in that matter. The conference programconsisted of keynote speeches and research papers selected by a severe double-blind reviewing process.Within these proceedings all the papers are published. By this, the proceedings give an interdisciplinaryoutline on the state of the art of dynamics in logistics as well as identify challenges and solutions forlogistics today and tomorrow.
Author: Sidney I. Resnick
Publisher: Springer Science & Business Media
ISBN: 0387242724
Category : Business & Economics
Languages : en
Pages : 412
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Book Description
This comprehensive text gives an interesting and useful blend of the mathematical, probabilistic and statistical tools used in heavy-tail analysis. It is uniquely devoted to heavy-tails and emphasizes both probability modeling and statistical methods for fitting models. Prerequisites for the reader include a prior course in stochastic processes and probability, some statistical background, some familiarity with time series analysis, and ability to use a statistics package. This work will serve second-year graduate students and researchers in the areas of applied mathematics, statistics, operations research, electrical engineering, and economics.
Author: Henk Zijm
Publisher: Springer
ISBN: 3319222880
Category : Technology & Engineering
Languages : en
Pages : 432
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Book Description
This contributed volume presents state-of-the-art advances in logistics theory in various fields as well as case studies. The book reports on a number of recently conducted studies in the Dinalog and the EffizienzCluster LogistikRuhr, thus bridging the gap between different perspectives of theoretical and applied research. A selection of theoretical topics, practical examples, case studies and project reports is presented in this volume. The editors carefully selected contributions from a wide variety of projects, which were carried out in both the Dinalog cluster and the Effizienzcluster LogistikRuhr. The contributions are grouped in five main sections, each representing key domains in the evolution of logistics and supply chain management: sustainability, urban logistics, value chain management, IT-based innovation, knowledge management. This book is intended for both researchers and practitioners in the field of logistics and supply chain management, to serve as an important source of information for further research as well as to stimulate further innovation.
Author: Frank Schneider
Publisher: Logos Verlag Berlin GmbH
ISBN: 3832536337
Category : Business & Economics
Languages : en
Pages : 172
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Book Description
Many tasks in operations management require the solution of complex optimization problems. Problems in which decisions are taken sequentially over time can be modeled and solved by dynamic programming. Real-world dynamic programming problems, however, exhibit complexity that cannot be handled by conventional solution techniques. This complexity may stem from large state and solution spaces, huge sets of possible actions, non-convexities in the objective function, and uncertainty. In this book, three highly complex real-world problems from the domain of operations management are modeled and solved by newly developed solution techniques based on stochastic dynamic programming. First, the problem of optimally scheduling participating demand units in an energy transmission network is considered. These units are scheduled such that total cost of supplying demand for electric energy is minimized under uncertainty in demand and generation. Second, the integrated problem of investment in and optimal operations of a network of battery swap stations under uncertain demand and energy prices is modeled and solved. Third, the inventory control problem of a multi-channel retailer selling through independent sales channels is modeled and optimality conditions for replenishment policies of simple structure are proven. This book introduces efficient approximation techniques based on approximate dynamic programming (ADP) and extends existing proximal point algorithms to the stochastic case. The methods are applicable to a wide variety of dynamic programming problems of high dimension.
