Optimization under Uncertainty

Optimization under Uncertainty presents a comprehensive overview of recent theoretical and computational advances in optimization under uncertainty. It places particular emphasis on scalar, vector, and set-valued optimization problems affected by uncertain data. In addition, the volume showcases a wide range of impactful applications, including inverse and control problems, variational inequalities, equilibrium models, network systems, and real-world challenges in engineering and biomedical sciences.

Features

• The book explores diverse applications, including inverse and control problems, medical imaging, equilibrium models, variational inequalities, and mechanical systems
• Thematic review chapters offer readers an in-depth understanding of key developments in the field
• Contributions from world-renowned researchers offer both expertise and high-quality insights.