Large Scale Optimization

Large-scale optimization focuses on efficiently finding optimal solutions to problems with numerous variables and constraints, arising across diverse fields like engineering, finance, and city management. Current research emphasizes developing robust and scalable algorithms, including those leveraging machine learning (e.g., deep learning, evolutionary algorithms, and decomposition methods) and quantum computing to address the computational challenges posed by these problems. These advancements are crucial for improving the efficiency and effectiveness of decision-making in complex systems, leading to better resource allocation, improved operational performance, and more informed policy decisions.