Robust optimization can be applied to a variety of OR problems that involve uncertainty, such as linear programming, integer programming, network optimization, scheduling, inventory ...

Unlike single-stage robust optimization under demand uncertainty, two-stage robust optimization allows one to control conservatism of the solutions by means of an allowed "budget for demand ...

Fidelity Optimization was used to run the optimization on the impeller shape. The design space consisted of 19 design variables, performed as multi-point optimizations, and three operating points on ...

We then develop a general model formulation, called robust optimization (RO), that explicitly incorporates the conflicting objectives of solution and model robustness. Robust optimization is compared ...

Abstract: We present a computationally efficient framework, called FlowDRO, for solving flow-based distributionally robust optimization (DRO) problems with Wasserstein uncertainty sets while aiming to ...