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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.
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.
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 sourcel#”
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