Flexible and Generalized Uncertainty Optimization

1 An Introduction to Generalized Uncertainty Optimization.- 2 Generalized Uncertainty Theory: A Language for Information Deficiency.- 3 The Construction of Flexible and Generalized Uncertainty Optimization Input Data.- 4 An Overview of Flexible and Generalized Uncertainty Optimization.- 5 Flexible Optimization.- 6 Generalized Uncertainty Optimization.- References.

Weldon Alexander Lodwick is a Full Professor of Mathematics at the University of Colorado Denver. He holds a Ph.D. degree in mathematics (1980) from the Oregon State University. He is the co-editor of the book Fuzzy Optimization: Recent Developments and Applications, Studies in Fuzziness and Soft Computing Vol. 254, Springer-Verlag Berlin Heidelberg, 2010, and the author of the book Interval and Fuzzy Analysis: A Unified Approach in Advances in Imaging and Electronic Physics, Vol. 148, pp. 76-192, Elsevier, 2007. His current research interests include interval analysis, distance geometry, as well as flexible and generalized uncertainty optimization. Over the last thirty years he has taught applied mathematical modeling to undergraduate and graduate students, which covers topics such as radiation therapy of tumor, fuzzy and possibilistic optimization modeling, global optimization, optimal control, molecular distance geometry problems, and neural networks applied to control problems.
Phantipa Thipwiwatpotjana is an Assistant Professor of Mathematics at the Chulalongkorn University, Bangkok, Thailand. She received her Ph. D. in Applied Mathematics from the University of Colorado Denver in 2010 for the dissertation titled "Linear programming problems for generalized uncertainty". She received scholarships from the Development and Promotion of Science and Technology Talents Project and Thai Government to study Mathematics for both undergraduate and graduate levels. Her primary research interests are in optimization under uncertainty, uncertainty relationship, and their applications.