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Scenario Logic and Probabilistic Management of Risk in Business and Engineering (Applied Optimization) - Hardcover
Synopsis
Book by Solojentsev, Evgueni D.
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From the Back Cover
The book proposes a uniform logic and probabilistic (LP) approach to risk estimation and analysis in engineering and economics. It covers the methodological and theoretical basis of risk management at the design, test, and operation stages of economic, banking, and engineering systems with groups of incompatible events (GIE). It considers the risk LP-models in classification, investment, management of companies, bribes and corruption, analysis of risk and efficiency of social and economical processes, and management of development. Key features of this Second Edition: -Five new chapters -Treatment of the basic principles of the modern risk LP theory (the LP-calculus, the LP-methods and the risk LP-theory with GIE) using uniform methodology and terminology with a practical orientation towards both engineering and economics, for the first time in book form -Clear definitions and notations, revised sections and chapters, an extended list of references, and a new subject index -More than a hundred illustrations and tables which motivate the presentation Specialists in risk management in economics, banking and business, as well as graduates and post-graduates in economics and engineering, will benefit from this book.
Review
From the reviews of the second edition: "The book proposes a uniform logic and probabilistic (LP) approach to risk estimation and analysis in engineering and economics. It covers the methodological and theoretical basis of risk management ... . the book is intended for experts in the field of risk management in business, technical, economic and organisational systems at the stages of design, test, debug and operation. Students, postgraduate students and teachers in economics and engineering fields may also benefit from this book." (Vangelis Grigoroudis, Zentralblatt MATH, Vol. 1156, 2009)
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Scenario Logic And Probabilistic Management Of Risk In Business And Engineering
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