Robust optimization (RO) is a useful methodology for formulating optimization problems in which some parameters are uncertain, but belong to a given uncertainty set. Two-stage RO models have received substantial attention in various application domains because of their ability to provide robust, reliable, and adaptable solutions. However, they are often challenging to solve. In this talk, I will introduce innovative and computationally efficient column-and-constraint generation (C&CG) algorithms for solving two-stage RO problems. C&CG algorithms operate within a master-subproblem framework. .

High-tech companies are investing in drone technologies for urban air delivery to address last-mile delivery issues and reduce road traffic congestion. Effective traffic management is crucial for scaling up these services in dense urban environments. This paper introduces a tube-based ConOps route network planning method, which decouples the NP-hard network planning problem into single-path problems and uses a space cost function for dense route design. Tests show this method generates near-optimal routes with significant computational time savings.