13 citations · 14 across the 16 of their papers we have counts for
7 papers · 1 filter
Symbolic Discovery of Iterative Algorithms: A Continuous Latent Space Bayesian Optimization Framework
Tongjia Liu, Ilias Mitrai
In this paper, we consider the automated discovery of iterative optimization algorithms. We formulate the algorithm discovery task as a discrete optimization problem and search for…
Feasibility-Aware Imitation Learning for Benders Decomposition
Bernard T. Agyeman, Zhe Li, Ilias Mitrai +1
Mixed-integer optimization problems arise in a wide range of control applications. Benders decomposition is a widely used algorithm for solving such problems by decomposing them in…
Graph-Based Imitation and Reinforcement Learning for Efficient Benders Decomposition
Bernard T. Agyeman, Zhe Li, Ilias Mitrai +1
This work introduces an end-to-end graph-based agent for accelerating the computational efficiency of Benders Decomposition. The agent's policy is parameterized by a graph neural n…
Learning to control inexact Benders decomposition via reinforcement learning
Zhe Li, Bernard T. Agyeman, Ilias Mitrai +1
Benders decomposition (BD), along with its generalized version (GBD), is a widely used algorithm for solving large-scale mixed-integer optimization problems that arise in the opera…
Taking the human out of decomposition-based optimization via artificial intelligence: Part II. Learning to initialize
Ilias Mitrai, Prodromos Daoutidis
The repeated solution of large-scale optimization problems arises frequently in process systems engineering tasks. Decomposition-based solution methods have been widely used to red…
Taking the human out of decomposition-based optimization via artificial intelligence: Part I. Learning when to decompose
Ilias Mitrai, Prodromos Daoutidis
In this paper, we propose a graph classification approach for automatically determining whether to use a monolithic or a decomposition-based solution method. In this approach, an o…
Computationally efficient solution of mixed integer model predictive control problems via machine learning aided Benders Decomposition
Ilias Mitrai, Prodromos Daoutidis
Mixed integer Model Predictive Control (MPC) problems arise in the operation of systems where discrete and continuous decisions must be taken simultaneously to compensate for distu…