42 citations · 190 across the 13 of their papers we have counts for
5 papers · 1 filter
Enhancing Constraint Programming via Supervised Learning for Job Shop Scheduling
Yuan Sun, Su Nguyen, Dhananjay Thiruvady +3
Constraint programming (CP) is a powerful technique for solving constraint satisfaction and optimization problems. In CP solvers, the variable ordering strategy used to select whic…
Adaptive Population-based Simulated Annealing for Uncertain Resource Constrained Job Scheduling
Dhananjay Thiruvady, Su Nguyen, Yuan Sun +3
Transporting ore from mines to ports is of significant interest in mining supply chains. These operations are commonly associated with growing costs and a lack of resources. Large…
Learning Generalizable Models for Vehicle Routing Problems via Knowledge Distillation
Jieyi Bi, Yining Ma, Jiahai Wang +4
Recent neural methods for vehicle routing problems always train and test the deep models on the same instance distribution (i.e., uniform). To tackle the consequent cross-distribut…
Ranking Constraint Relaxations for Mixed Integer Programs Using a Machine Learning Approach
Jake Weiner, Andreas T. Ernst, Xiaodong Li +1
Solving large-scale Mixed Integer Programs (MIP) can be difficult without advanced algorithms such as decomposition based techniques. Even if a decomposition technique might be app…
Adaptive Solution Prediction for Combinatorial Optimization
Yunzhuang Shen, Yuan Sun, Xiaodong Li +2
This paper aims to predict optimal solutions for combinatorial optimization problems (COPs) via machine learning (ML). To find high-quality solutions efficiently, existing work use…