A graduate text on theory and methods using applied probability techniques for scheduling service, manufacturing, and information networks.

This accessible book aims to collect in a single volume the essentials of stochastic networks. Stochastic networks have become widely used as a basic model of many physical systems in a diverse range of fields. Written by leading authors in the field, this book is meant to be used as a reference or supplementary reading by practitioners in operations research, computer systems, communications networks, production planning, and logistics.

Eugene A. Feinberg Adam Shwartz This volume deals with the theory of Markov Decision Processes (MDPs) and their applications. Each chapter was written by a leading expert in the re spective area. The papers cover major research areas and methodologies, and discuss open questions and future research directions. The papers can be read independently, with the basic notation and concepts ofSection 1.2. Most chap ters should be accessible by graduate or advanced undergraduate students in fields of operations research, electrical engineering, and computer science. 1.1 AN OVERVIEW OF MARKOV DECISION PROCESSES The theory of Markov Decision Processes-also known under several other names including sequential stochastic optimization, discrete-time stochastic control, and stochastic dynamic programming-studiessequential optimization ofdiscrete time stochastic systems. The basic object is a discrete-time stochas tic system whose transition mechanism can be controlled over time. Each control policy defines the stochastic process and values of objective functions associated with this process. The goal is to select a "good" control policy. In real life, decisions that humans and computers make on all levels usually have two types ofimpacts: (i) they cost orsavetime, money, or other resources, or they bring revenues, as well as (ii) they have an impact on the future, by influencing the dynamics. In many situations, decisions with the largest immediate profit may not be good in view offuture events. MDPs model this paradigm and provide results on the structure and existence of good policies and on methods for their calculation.

From foundations to state-of-the-art; the tools and philosophy you need to build network models.

This book is dedicated to Jinhua Cao on the occasion of his 80th birthday. Jinhua Cao is one of the most famous reliability theorists. His main contributions include: published over 100 influential scientific papers; published an interesting reliability book in Chinese in 1986, which has greatly influenced the reliability of education, academic research and engineering applications in China; initiated and organized Reliability Professional Society of China (the first part of Operations Research Society of China) since 1981. The high admiration that Professor Cao enjoys in the reliability community all over the world was witnessed by the enthusiastic response of each contributor in this book. The contributors are leading researchers with diverse research perspectives. The research areas of the book iclude a broad range of topics related to reliability models, queueing theory, manufacturing systems, supply chain finance, risk management, Markov decision processes, blockchain and so forth. The book consists of a brief Preface describing the main achievements of Professor Cao; followed by congratulations from Professors Way Kuo and Wei Wayne Li, and by Operations Research Society of China, and Reliability Professional Society of China; and further followed by 25 articles roughly grouped together. Most of the articles are written in a style understandable to a wide audience. This book is useful to anyone interested in recent developments in reliability, network security, system safety, and their stochastic modeling and analysis.

The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that show the spectrum of research, the richness of ideas, and the breadth of applications that has come from this field. The second edition builds on the success of the former edition with more than 150 completely new entries, designed to ensure that the reference addresses recent areas where optimization theories and techniques have advanced. Particularly heavy attention resulted in health science and transportation, with entries such as "Algorithms for Genomics", "Optimization and Radiotherapy Treatment Design", and "Crew Scheduling".

Computer system performance evaluation is a key discipline for the understanding of the behavior and limitations of large scale computer systems and networks. This volume provides an overview of the milestones and major developments of the field. The contributions to the book include many of the principal leaders from industry and academia with a truly international coverage, including several IEEE and ACM Fellows, two Fellows of the US National Academy of Engineering and a Fellow of the European Academy, and a former President of the Association of Computing Machinery. Sample Chapter(s). Chapter 1: Ken Sevcik as an Advisor and Mentor (252 KB). Contents: Ken Sevcik as an Advisor and Mentor (E Lazowska et al.); Shadow Servers and Priority Scheduling (J P Buzen); On the Chronology of Dynamic Allocation Index Policies: The Pioneering Work of K C Sevcik (E Coffman); Operational Analysis (P J Denning); Function Approximation by Random Neural Networks with a Bounded Number of Layers (E Gelenbe et al.); The Achilles'' Heel of Computer Performance Modeling and the Model Building Shield (V De Nitto Person & G Lazeolla); Wireless Network Simulation: Towards a Systematic Approach (S K Tripathi et al.); Location- and Power-Aware Protocols for Wireless Networks with Asymmetric Links (G Wang et al.); Multi-Threaded Servers with High Service Time Variation for Layered Queueing Networks (G Franks et al.); Quantiles of Sojourn Times (P G Harrison & W J Knottenbelt); Asymptotic Solutions for Two Non-Stationary Problems in Internet Reliability (Y Kogan & G Choudhury); Burst Loss Probabilities in an OBS Network with Dynamic Simultaneous Link Possession (T Battestilli & H Perros); Stochastic Analysis of Resource Allocation in Parallel Processing Systems (M S Squillante); Periodic Task Cluster Scheduling in Distributed Systems (H Karatza). Readership: Graduate students, Internet engineers, computer scientists, system engineers, and computer designers. Also suitable for use in professional development seminars in computers and networks."

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.

In this volume, leading experts in mathematical manufacturing research and related fields review and update recent advances of mathematics in stochastic manufacturing systems and attempt to bridge the gap between theory and applications. The topics covered include scheduling and production planning, modeling of manufacturing systems, hierarchical control for large and complex systems, Markov chains, queueing networks, numerical methods for system approximations, singular perturbed systems, risk-sensitive control, stochastic optimization methods, discrete event systems, and statistical quality control.

Articles of mathematical interest as well as operations research and management science.