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Thisbook shows how common operation management methods and algorithms can beextended to deal with vague or imprecise information in decision-makingproblems. It describes how to combine decision trees, clustering,multi-attribute decision-making algorithms and Monte Carlo Simulation with themathematical description of imprecise or vague information, and how tovisualize such information. Moreover, it discusses a broad spectrum ofreal-life management problems including forecasting the apparentconsumption of steel products, planning and scheduling of production processes,project portfolio selection and economic-risk estimation. It is a concise, yetcomprehensive, reference source for researchers in decision-making anddecision-makers in business organizations alike.
List of contents
Fuzzy Numbers.- Ordering of Fuzzy Numbers.- FuzzyRandom Variable and the Dempster-Shafer Theory of Evidence.- Multi-Attribute Decision Making Process and itsApplication.- Risk Assessment in the Presence of Uncertainty.- Applicationof Fuzzy Theory in Steel Production Planning and Scheduling.- Applicationof Fuzzy Decision Trees in Analog Forecasting.- Selected Issues ofVisualisation of Fuzziness in Cardiac Imaging Data.
Summary
This
book shows how common operation management methods and algorithms can be
extended to deal with vague or imprecise information in decision-making
problems. It describes how to combine decision trees, clustering,
multi-attribute decision-making algorithms and Monte Carlo Simulation with the
mathematical description of imprecise or vague information, and how to
visualize such information. Moreover, it discusses a broad spectrum of
real-life management problems including forecasting the apparent
consumption of steel products, planning and scheduling of production processes,
project portfolio selection and economic-risk estimation. It is a concise, yet
comprehensive, reference source for researchers in decision-making and
decision-makers in business organizations alike.
