Looks at quality management in a new way; Offers a very different mathematical tool set than traditionally employed for quality control problems; Yao is a leading researcher in the area of stochastic modeling and the author of a previous Springer book
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.
This book examines the fundamental mathematical and stochastic process techniques needed to study the behavior of extreme values of phenomena based on independent and identically distributed random variables and vectors. It emphasizes the core primacy of three topics necessary for understanding extremes: the analytical theory of regularly varying functions; the probabilistic theory of point processes and random measures; and the link to asymptotic distribution approximations provided by the theory of weak convergence of probability measures in metric spaces.
This book focuses on planning and scheduling applications. Planning and scheduling are forms of decision-making that play an important role in most manufacturing and services industries. The planning and scheduling functions in a company typically use analytical techniques and heuristic methods to allocate its limited resources to the activities that have to be done. The application areas considered in this book are divided into manufacturing applications and services applications. The book covers five areas in manufacturing: project scheduling, job shop scheduling, scheduling of flexible assembly systems, economic lot scheduling, and planning and scheduling in supply chains. It covers four areas in services: reservations and timetabling, tournament scheduling, planning and scheduling in transportation, and workforce scheduling. At the end of each chapter, a case study or a system implementation is described in detail. Numerous examples and exercises throughout the book illustrate the material presented. The fundamentals concerning the methodologies used in the application chapters are covered in the appendices. The book comes with a CD-ROM that contains various sets of powerpoint slides. The CD also contains several planning and scheduling systems that have been developed in academia as well as generic optimization software that has been developed in industry. This book is suitable for more advanced students in industrial engineering and operations research as well as graduate students in business. Michael Pinedo is the Julius Schlesinger Professor of Operations Management in the Stern School of Business at New York University. His research interests lie in the theoretical and applied aspects of planning and scheduling. He has written numerous papers on the theory of deterministic and stochastic scheduling and has also consulted extensively in industry. He has been actively involved in the development of several large industrial planning and scheduling systems.
Apart from a thorough exploration of all the important concepts, this volume includes over 75 algorithms, ready for putting into practice. The book also contains numerous hands-on implementations of selected algorithms to demonstrate applications in realistic settings. Readers are assumed to have a sound understanding of calculus, introductory matrix analysis, and intermediate statistics, but otherwise the book is self-contained. Suitable for graduates and undergraduates in mathematics and engineering, in particular operations research, statistics, and computer science.
This books covers the broad range of research in stochastic models and optimization. Applications presented include networks, financial engineering, production planning, and supply chain management. Each contribution is aimed at graduate students working in operations research, probability, and statistics.
Focuses on theoretical results along with applications All the main topics covering the heart of the subject are introduced to the reader in a systematic fashion Concentration is on the probabilistic and statistical aspects of extreme values Excellent introduction to extreme value theory at the graduate level, requiring only some mathematical maturity
* 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