Bücher der Reihe Springer Series in Operations Research and Financial Engineering

"This is an excellent and well-written text on discrete event simulation with a focus on applications in Operations Research. Methods are provided for generating pseudo-random numbers (including combining such streams) and for generating random numbers from most standard statistical distributions."

This richly illustrated book introduces the subject of optimization to a broad audience with a balanced treatment of theory, models and algorithms. Through numerous examples from statistical learning, operations research, engineering, finance and economics, the text explains how to formulate and justify models while accounting for real-world considerations such as data uncertainty. It goes beyond the classical topics of linear, nonlinear and convex programming and deals with nonconvex and nonsmooth problems as well as games, generalized equations and stochastic optimization.The book teaches theoretical aspects in the context of concrete problems, which makes it an accessible onramp to variational analysis, integral functions and approximation theory. More than 100 exercises and 200 fully developed examples illustrate the application of the concepts. Readers should have some foundation in differential calculus and linear algebra. Exposure to real analysiswould be helpful but is not prerequisite.

This new edition offers updated content and an outlook on further results, extensions and generalizations on stopped random walks. It also contains a new chapter on perturbed random walks and nearly 100 new bibliographic references.

This book analyzes and compares four closely related problems, namely linear programming, integer programming, linear integration, and linear summation (or counting). The book provides some new insights on duality concepts for integer programs.

In an extensively updated new edition, this book teaches stochastic programming, with new approaches for discrete variables, new results on risk measures in modeling and Monte Carlo sampling methods, a new chapter on relationships to other methods and more.

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

In recent years, a number of interesting decision aids have become available to assist in such decisions. The aim of this book is to provide a comparative survey of many of the decision aids currently available. Subsequent chapters then focus on specific decision aids and demonstrate some of the software which implement these ideas.

This text develops the mathematical implications of barriers to the geometrical and analytical characteristics of continuous location problems. The book will appeal to those working in operations research and management science, and mathematicians interested in optimization theory and its applications.

This book provides an introduction to MIP modeling and to planning systems, a unique collection of reformulation results, and an easy to use problem-solving library. This approach is demonstrated through a series of real life case studies, exercises and detailed illustrations.

Written by a leading researcher this book presents an introduction to Stochastic Petri Nets covering the modeling power of the proposed SPN model, the stability conditions and the simulation methods. Appeals to a wide range of researchers in engineering, computer science, mathematics and OR.

Manufacturing industries are devoted to producing high-quality products in the most economical and timely manner. In fact, we see an increasing number of manufacturing systems engineering departments and manufacturing research centers in universities not only in the US but also in Europe, Japan, and many developing countries.

From the reviews: "The material is self-contained, but it is technical and a solid foundation in probability and queuing theory is beneficial to prospective readers. [... It] is intended to be accessible to those with less background. This book is a must to researchers and graduate students interested in these areas." ISI Short Book Reviews

This volume presents its author's pioneering stochastic approach to global optimization across a range of disciplines, including mathematics and engineering. The new method confronts constrained and unconstrained problems and unifies our conceptual framework.

This book covers the classical theory of Markov chains on general state-spaces as well as many recent developments. Part I lays the foundations of the theory of Markov chain on general states-space. Part II covers the basic theory of irreducible Markov chains on general states-space, relying heavily on regeneration techniques.

This book reviews basic terminology, concepts, taxonomy and tenets of inventory systems, then explores models: EOQ, lot-sizing, Newsvendor, continuous time and more. The authors discuss in detail different real situations in industry and theoretical models.

This is part two of a two-volume work presenting a comprehensive treatment of the finite-dimensional variational inequality and complementarity problem. It details algorithms for solving finite dimensional variational inequalities and complementarity problems.

Numerical Optimization presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. There are new chapters on nonlinear interior methods and derivative-free methods for optimization, both of which are used widely in practice and the focus of much current research.

Part III presents direct search methods (Generalized Pattern Search and Mesh Adaptive Direct Search) and Part IV focuses on model-based methods (Simplex Gradient and Trust Region).

This work considers Kronecker-based models with finite as well as countably infinite state spaces for multidimensional Markovian systems by paying particular attention to those whose reachable state spaces are smaller than their product state spaces.

The book examines the performance and optimization of systems where queueing and congestion are important constructs.

The book examines the performance and optimization of systems where queueing and congestion are important constructs.

Implicit Functions and Solution Mappings

This book bridges theory and application of stochastic programming in operations research. It describes various methods of formulating stochastic optimization problems, and illustrates their advantages and disadvantages with examples and case studies.

This work considers Kronecker-based models with finite as well as countably infinite state spaces for multidimensional Markovian systems by paying particular attention to those whose reachable state spaces are smaller than their product state spaces.

This book, written for the logistics manager and researcher, presents an authoritative survey of the modern theory and application of logistics, including case studies in which decision support tools for large-scale logistics applications are developed.

Presents a treatment of extreme value theory that focuses on some beautiful theoretical results along with applications. This title concentrates on the probabilistic and statistical aspects of extreme values. It offers introduction to extreme value theory at the graduate level.

This book offers principles and useful methods for making investment and risk management decisions in the presence of hedgeable and non-hedgeable risks using the simplest possible methods and models that capture the essential features of real-world problems.

The new edition of this book presents a comprehensive and up-to-date description of the most effective methods in continuous optimization. It is enhanced by new chapters on nonlinear interior methods and derivative-free methods for optimization.

Encompassing all the major topics students will encounter in courses on the subject, the authors teach both the underlying mathematical foundations and how these ideas are implemented in practice.