David D. Yao – författare

Two of the most exciting topics of current research in stochastic networks are the complementary subjects of stability and rare events. Both are classical topics that have experienced renewed interest motivated by new applications to emerging technologies. For example, new stability issues arise in the scheduling of multiple classes in semiconductor manufacturing, the so-called "re-entrant lines," and a prominent need for studying rare events is associated with the design of telecommunication systems using the new ATM (asynchronous transfer mode) technology so as to guarantee quality of service. The objective of this volume is to present a sample of recent research problems, methodologies, and results in these two exciting and burgeoning areas. This volume originated from a workshop held at Columbia University in 1995 organized by Columbia's Center for Applied Probability.

This accessible and timely book collects in a single volume the essentials of stochastic networks, from the classical product-form theory to the more recent developments such as diffusion and fluid limits, stochastic comparisons, stability, control (dynamic scheduling) and optimization.The book was developed from the authors' teaching stochastic networks over many years. It will be useful to students from engineering, business, mathematics, and probability and statistics. As stochastic networks have become widely used as a basic model of many physical systems in a diverse range of fields, the book can also be used as a reference or supplementary readings for courses in operations research, computer systems, communication networks, production planning and logistics, and by practitioners in the field.

Quality control is a scientific means for conducting observations, tests, and inspections and thereby making decisions that improve the perfomance of industrial processes. This book develops a set of dynamic approaches characterized by coordination. In practice, quality control problems almost never exist in isolation. The basic methodology underlying the studies is Markov decision programming. The book can be used as a graduate text for a new course on statistical process control, or as a reference for researchers and practitioners in mathematics, operations research and operations management, quality control, production planning, and logistics.

This book covers the broad range of research in stochastic models and optimization. Applications covered include networks, financial engineering, production planning and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.

Information previously available only in journal articles and research papers has been brought together in this outstanding text. Uses the unifying theme of monotone structure to transcend the two-perspective approach to DES--one stressing logical/qualitative issues and the other temporal/quantitative analysis--to encompass elements from both. Features notes and references at the end of each chapter.

In the foreword to this book, Professor Paul Zipkin notes three global changes that have enabled the recent vast developments in the field of supply chains. Moreover, these changes may be only the beginning and more change is likely in the fast-moving field of supply chain management. These global changes are: the explosive growth of the Internet; the growth in free-market economies with the corresponding political interest in global economic stability; and the emergence of a global managerial culture focused on performance, quality and service. Each of the articles in this book offers an illuminating way to think about the key issues in supply chain management. Some also offer practical techniques to solve important problems. Together they provide a survey of the current state of the art in research and practice.

The editors have taken the occasion of Professor John A. Buzacott's retirement as a motivating event to develop this volume. The objective of this text is to both honour John Buzacott's achievements and to publish a set of chapters on cutting-edge topics in the field of manufacturing and supply chain management. The book is organized into two parts. The first part focuses on aspects of manufacturing systems modelling. This part includes chapters on the evolution of manufacturing systems modelling, queuing network models and related software technologies, two-moment approximation for fork/join queues, and asymptotic optimality of a scheduling policy. The second part focuses on production-inventory systems and supply chains.This second section includes chapters on a multi-echelon logistics system, optimal control of a substitutable inventory system, structured assemble-to-order systems, the impact of advance demand information on various production-inventory control mechanisms, the quality of demand information as it impacts flexible contracts, the supply of information goods using spot and forward pricing strategies, modelling frameworks that connect material flows with financial information flows.

The objective of this book is to collect in a single volume the essentials of stochastic networks, from the classical product-form theory to the more re­ cent developments such as diffusion and fluid limits, stochastic comparisons, stability, control (dynamic scheduling) and optimization. The selection of materials inevitably is a reflection upon our bias and preference, but it is also driven to a large extent by our desire to provide a graduate-level text that is well balanced in breadth and depth, suitable for the classroom. Given the wide-ranging applications of stochastic networks in recent years, from supply chains to telecommunications, it is also our hope that the book will serve as a useful reference for researchers and students alike in these diverse fields. The book consists of three parts. The first part, Chapters 1 through 4, covers (continuous-time) Markov-chain models, including the classical Jackson and Kelly networks, the notion of quasi-reversible queues, and stochastic comparisons. The second part, Chapters 5 through 10, focuses on Brownian models, including limit theorems for generalized Jackson net­ works and multiclass feedforward networks, an in-depth examination of stability in a Kumar-Seidman network, and Brownian approximations for general multiclass networks with a mixture of priority and first-in-first-out disciplines. The third part, Chapters 11 and 12, discusses scheduling in both queueing (stochastic) and fluid (deterministic) networks, along with topics such as conservation laws, polymatroid optimization, and linear pro­ gramming.

The objective of this volume is to highlight through a collection of chap­ ters some of the recent research works in applied prob ability, specifically stochastic modeling and optimization. The volume is organized loosely into four parts. The first part is a col­ lection of several basic methodologies: singularly perturbed Markov chains (Chapter 1), and related applications in stochastic optimal control (Chapter 2); stochastic approximation, emphasizing convergence properties (Chapter 3); a performance-potential based approach to Markov decision program­ ming (Chapter 4); and interior-point techniques (homogeneous self-dual embedding and central path following) applied to stochastic programming (Chapter 5). The three chapters in the second part are concerned with queueing the­ ory. Chapters 6 and 7 both study processing networks - a general dass of queueing networks - focusing, respectively, on limit theorems in the form of strong approximation, and the issue of stability via connections to re­ lated fluid models. The subject of Chapter 8 is performance asymptotics via large deviations theory, when the input process to a queueing system exhibits long-range dependence, modeled as fractional Brownian motion.

In the foreword to Supply Chain Structures, Professor Paul Zipkin notes three global changes that have enabled the recent vast developments in the field of supply chains. Moreover, these changes may be only the beginning and more change is likely in the fast-moving field of supply chain management. These global changes are: the explosive growth of the Internet; the growth in free-market economies with the corresponding political interest in global economic stability; and the emergence of a global managerial culture focused on performance, quality, and service. Professor Zipkin goes on to say "In Supply Chain Structures, the editors Jeannette Song and David Yao have collected a spectrum of approaches to these challenges from some of the leading scholars of supply chains, from both the academic and commercial worlds. Each of the articles offers an interesting and illuminating way to think about the key issues in supply chain management. Some also offer practical techniques to solve important problems. Together they provide an excellent survey of the current state of the art in research and practice."

Manufacturing systems have become increasingly complex over recent years. This volume presents a collection of chapters which reflect the recent developments of probabilistic models and methodologies that have either been motivated by manufacturing systems research or been demonstrated to have significant potential in such research. The editor has invited a number of leading experts to present detailed expositions of specific topics. These include: Jackson networks, fluid models, diffusion and strong approximations, the GSMP framework, stochastic convexity and majorization, perturbation analysis, scheduling via Brownian models, and re-entrant lines and dynamic scheduling. Each chapter has been written with graduate students in mind, and several have been used in graduate courses that teach the modeling and analysis of manufacturing systems.

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.

Quality control is a scientific means for conducting observations, tests, and inspections and thereby making decisions that improve the perfomance of industrial processes. This book develops a set of dynamic approaches characterized by coordination. In practice, quality control problems almost never exist in isolation. The basic methodology underlying the studies is Markov decision programming. The book can be used as a graduate text for a new course on statistical process control, or as a reference for researchers and practitioners in mathematics, operations research and operations management, quality control, production planning, and logistics.