5 citations · 10 across the 12 of their papers we have counts for
4 papers · 1 filter
Approximate Dynamic Optimization via Deep Neural Operators
Amin Nassaji, Ilias Mitrai, Prodromos Daoutidis
This paper addresses the solution of nonlinear dynamic optimization problems that compute optimal manipulated input profiles to enforce desired output profiles. Such trajectory opt…
A Hybrid Reinforcement and Self-Supervised Learning Aided Benders Decomposition Algorithm
Bernard T. Agyeman, Zhe Li, Ilias Mitrai +1
We propose a hybrid reinforcement and self-supervised learning framework for accelerating generalized Benders decomposition (GBD). In this framework, a graph based reinforcement le…
Accelerating process control and optimization via machine learning: A review
Ilias Mitrai, Prodromos Daoutidis
Process control and optimization have been widely used to solve decision-making problems in chemical engineering applications. However, identifying and tuning the best solution alg…
Fast and Stable Nonconvex Constrained Distributed Optimization: The ELLADA Algorithm
Wentao Tang, Prodromos Daoutidis
Distributed optimization, where the computations are performed in a localized and coordinated manner using multiple agents, is a promising approach for solving large-scale optimiza…