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.

cutting-edge research in fuzzy decision theory and applications how to deal with uncertain and incomplete information in decision-making Includes practical case-studies on real-life management problems Includes supplementary material: sn.pub/extras

Inhalt

Fuzzy Numbers.- Ordering of Fuzzy Numbers.- Fuzzy Random Variable and the Dempster-Shafer Theory of Evidence.- Multi-Attribute Decision Making Process and its Application.- Risk Assessment in the Presence of Uncertainty.- Application of Fuzzy Theory in Steel Production Planning and Scheduling.- Application of Fuzzy Decision Trees in Analog Forecasting.- Selected Issues of Visualisation of Fuzziness in Cardiac Imaging Data.