Generative ai and process systems engineering: The next frontier
This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …
such as large language models (LLMs), can enhance solution methodologies within process …
A deep instance generative framework for milp solvers under limited data availability
In the past few years, there has been an explosive surge in the use of machine learning (ML)
techniques to address combinatorial optimization (CO) problems, especially mixed-integer …
techniques to address combinatorial optimization (CO) problems, especially mixed-integer …
Large-scale dynamic scheduling for flexible job-shop with random arrivals of new jobs by hierarchical reinforcement learning
As the intelligent manufacturing paradigm evolves, it is urgent to design a near real-time
decision-making framework for handling the uncertainty and complexity of production line …
decision-making framework for handling the uncertainty and complexity of production line …
Learning to configure separators in branch-and-cut
Cutting planes are crucial in solving mixed integer linear programs (MILP) as they facilitate
bound improvements on the optimal solution. Modern MILP solvers rely on a variety of …
bound improvements on the optimal solution. Modern MILP solvers rely on a variety of …
Learning to optimize: A tutorial for continuous and mixed-integer optimization
Learning to optimize (L2O) stands at the intersection of traditional optimization and machine
learning, utilizing the capabilities of machine learning to enhance conventional optimization …
learning, utilizing the capabilities of machine learning to enhance conventional optimization …
Machine learning for cutting planes in integer programming: A survey
We survey recent work on machine learning (ML) techniques for selecting cutting planes (or
cuts) in mixed-integer linear programming (MILP). Despite the availability of various classes …
cuts) in mixed-integer linear programming (MILP). Despite the availability of various classes …
De novo molecular generation via connection-aware motif mining
De novo molecular generation is an essential task for science discovery. Recently, fragment-
based deep generative models have attracted much research attention due to their flexibility …
based deep generative models have attracted much research attention due to their flexibility …
Reinforcement Learning within Tree Search for Fast Macro Placement
Macro placement is a crucial step in modern chip design, and reinforcement learning (RL)
has recently emerged as a promising technique for improving the placement quality …
has recently emerged as a promising technique for improving the placement quality …
[HTML][HTML] Machine learning augmented branch and bound for mixed integer linear programming
Abstract Mixed Integer Linear Programming (MILP) is a pillar of mathematical optimization
that offers a powerful modeling language for a wide range of applications. The main engine …
that offers a powerful modeling language for a wide range of applications. The main engine …
Learning to stop cut generation for efficient mixed-integer linear programming
Cutting planes (cuts) play an important role in solving mixed-integer linear programs
(MILPs), as they significantly tighten the dual bounds and improve the solving performance …
(MILPs), as they significantly tighten the dual bounds and improve the solving performance …