When it comes to optimization techniques, in some cases, the available information from real models may not be enough to construct either a probability distribu

The volume presents a collaboration between internationally recognized experts on anti-optimization and structural optimization, and summarizes various novel id

In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. T

Robust optimization is still a relatively new approach to optimization problems affected by uncertainty, but it has already proved so useful in real application

This book presents the theory and methods of flexible and generalized uncertainty optimization. Particularly, it describes the theory of generalized uncertainty