Full Description
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.
Contents
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.
