Bücher der Reihe International Series in Operations Research & Management Science

Brings together reviews and the advances by leading experts on the fundamental theories, methodologies and applications of MCDM. This title is aimed at graduate students and researchers in mathematics, economics, management and engineering, as well as at practicing management scientists who wish to better understand the principles of this field.

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.

In two volumes, Planning Production and Inventories in the Extended Enterprise: A State of the Art Handbook examines production planning across the extended enterprise against a backdrop of important gaps between theory and practice. Production Planning Effects on Dynamic Behavior of A Simple Supply Chain;

This new edition is expanded and updated, complete with end-of-chapter exercises. Outlines the recent development of Markov chain models for modeling queueing systems, manufacturing and re-manufacturing systems, inventory systems and financial risk management.

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.

A key area of research in OR/MS, MCDM is now being applied in many new areas, including GIS systems, AI, and group decision making.This volume is in effect the third in a series of Springer books by these editors (all in the ISOR series), and it brings all the latest developments in MCDM into focus.

This book surveys state-of-the-art optimization modeling for design, analysis, and management of wireless networks, such as cellular and wireless local area networks (LANs), and the services they deliver.

Queueing network models have been widely applied as a powerful tool for modelling, performance evaluation, and prediction of discrete flow systems, such as computer systems, communication networks, production lines, and manufacturing systems.

Written by a leading authority on applying operational research to risk management, this book sets out improved methods of risk analysis that avoid the many pitfalls in assessing and managing risk where the probabilities of consequences are hard to define.

This book is dedicated to improving healthcare through reducing the delays experienced by patients. It is the first book treatment to have reduction in patient delay as its sole focus, and therefore, provides the foundation by which hospitals can implement change.

Hidden Markov Models in Finance offers the first systematic application of these methods to specialized financial problems: option pricing, credit risk modeling, volatility estimation and more.

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.