Risk Modeling, Assessment, and Management

Risk Modeling, Assessment, and Management describes the state of the art of risk analysis, a rapidly growing field with important applications in engineering, science, manufacturing, business, management, and public policy. Unlike any other text on the subject, this definitive work integrates the art and science of risk analysis. It shows clearly how to quantify risk and construct probability in conjunction with real-world decision-making problems, including a host of institutional, organizational, political, and cultural considerations. Presenting basic concepts as well as advanced material, avoiding higher mathematics whenever possible, and incorporating numerous examples and case studies to illustrate the analytical methods under discussion, this remarkable book:

• Unites the latest theories and methodologies from diverse disciplines
• Addresses professionals at different levels of mathematical ability
• Explains how to identify real, perceived, and imaginary risks
• Details the most effective and least expensive approaches to risk management
• Offers extensive coverage of the modeling process
• Considers the role of government and regulatory agencies in risk management
• Introduces the conditional expected value method as a supplement to the mathematical expectation formula.

Timely, comprehensive, and supplemented with more than 200 figures, Risk Modeling, Assessment, and Management is an essential reference for professionals working in universities, industry, and government; and for anyone interested in risk analysis in virtually any discipline

YACOV Y. HAIMES, PhD, PE, has taught risk analysis for more than 25 years. He is the Lawrence R. Quarles Professor of Systems Engineering and Civil Engineering and the founding Director (1987) of the Center for Risk Management of Engineering Systems at the University of Virginia. Extensively involved in research and consulting work for government and industry, he is the author of numerous books, including Hierarchical Multiobjective Analysis of Large-Scale Systems.