Bøger i International Series in Operations Research & Management Science serien

This book will be the standard reference book on the topic for both researchers and sophisticated practitioners, and it will be used as a textbook in courses or seminars focusing on this topic.

Here is the first systematic handbook treatment of quantitative modeling natural resource problems, their allocated efficient use, and societal and economic impact. The book covers these areas with contributions from researchers on, among others, modeling natural research problems, quantifying data, and developing algorithms.

This edited volume captures and communicates the best thinking on how to improve healthcare by improving the delivery of services -- providing care when and where it is needed most -- through application of state-of-the-art scheduling 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.

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.

Risk Analysis: Foundations, Models, and Methods fully addresses the questions of "What is health risk analysis?" Risk management applies principles for choosing among alternative decision alternatives or actions that affect exposure, health risks, or their consequences.

Constraint Programming is a problem-solving paradigm that establishes a clear distinction between two pivotal aspects of a problem: (1) a precise definition of the constraints that define the problem to be solved and (2) the algorithms and heuristics enabling the selection of decisions to solve the problem.

Among the latter, we find some well-known decision support techniques: cost-benefit analysis, multiple criteria decision analysis, decision trees, .

Models, Methods, Concepts and Applications of the Analytic Hierarchy Process is a volume dedicated to selected applications of the Analytic Hierarchy Process (AHP) focused on three themes: economics, the social sciences, and the linking of measurement with human values.

The standard view of Operations Research/Management Science (OR/MS) dichotomizes the field into deterministic and probabilistic (nondeterministic, stochastic) subfields.

Entropy optimization is a useful combination of classical engineering theory (entropy) with mathematical optimization.

This book applies stochastic models and analytical techniques to such areas of manufacturing as facilities planning, transportation and material handling systems, production scheduling, logistics, supply chain management and productivity and quality models.

From the Preface:Collectively, the chapters in this book address application domains including inpatient and outpatient services, public health networks, supply chain management, and resource constrained settings in developing countries.

This book aims to demonstrate and detail the pervasive nature of Discrete Optimization. It is done with an academic treatment outlining the state-of-the-art for researchers across the domains of the Computer Science, Math Programming, Applied Mathematics, Engineering, and Operations Research.

This book presents the state of the art in the application of operations research models to preventing terrorist attacks, planning and preparing for emergencies and responding to and recovering from disasters. Covers preparedness, relief efforts and more.

This concept has come to represent the two major features underlying the notion of a project: the sequential and the competitive nature of its components, the project's activities.

Consideration was given to more advanced theoretical approaches and novel applications of reliability to ensure that topics having a futuristic impact were specifically included.

A Simple Model of Electric Power Network . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Power flow equations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 Social welfare action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 A Market Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50 An efficient trading rule . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51 Competitive equilibrium and social optimum . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 A Dynamic Trading Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54 An Illustrative Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56 Alternative Implementation Plans . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Appendix . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 60 References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64 Chapter 5: The Berlin Mandate: The Design ofCost-Effictive Mitigation Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68 The Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Future Emissions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70 The Costs of Alternative Commitments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Some Final Comments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Endnotes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Chapter 6: Some Implications of Improved CO] Emissions Control Technology in The Context of Global Climate Change . . . . . . . . . . . . . . . . . . . . 85 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Sample-Path Analysis of Queueing Systems uses a deterministic (sample-path) approach to analyze stochastic systems, primarily queueing systems and more general input-output systems.

Equilibrium is a concept used in operations research and economics to understand the interplay of factors and problems arising from competitive systems in the economic world. new mathematical methods allowing researchers to combine other theoretical approaches with the projected dynamical systems approach;

The purpose of this handbook is to define transportation as a scientific discipline that transcends transportation technology and methods. The science of transportation defines these properties, and demonstrates how our knowledge of one mode of transportation can be used to explain the behavior of another.

Over the past thirty-five years, a substantial amount of theoretical and empirical scholarly research has been developed across the discipline domains of Transportation. The Handbook of Transportation Science outlines the field of transportation as a scientific discipline that transcends transportation technology and methods.

A nice night of October 2007, in Beijing, during the XV World Conference on ITS a number of colleagues met informally for a dinner party that spontaneously became a vivid discussion on the importance of traffic data for all types of p- poses.