Orateur
Kibaek Kim
(Argonne National Laboratory)
Description
Large-scale mixed-integer programs (MIPs) pose significant computational challenges due to their complexity, nonconvexity, and nonsmooth dual functions. Traditional decomposition methods often suffer from slow convergence, sensitivity to parameters, and instability. We propose Bundle-ADMM, a novel method combining the Alternating Direction Method of Multipliers (ADMM) and bundle techniques to stabilize dual updates and accelerate convergence. Computational results on electric grid planning problems demonstrate that Bundle-ADMM significantly improves stability and convergence efficiency compared to conventional approaches.
Authors
Hideaki Nakao
Kibaek Kim
(Argonne National Laboratory)
