Exploiting Symmetry in Large-Scale Optimization and Control
This talk will present theoretical and algorithmic results on exploiting symmetry to reduce the computational complexity large-scale control and optimization problems. First, we will show how symmetry can be used to reduce the memory complexity of explicit solutions of optimization problems. Second, we will show how symmetry can be used to reduce the memory and computational complexity of an alternating direction method of multipliers (ADMM) optimization algorithm. These techniques will be demonstrated for two applications: network balancing and heating, ventilation, and air-conditioning (HVAC).