Search Results for author:
Found 4 papers, 0 papers with code
Enhancing Constraint Programming via Supervised Learning for Job Shop Scheduling
Finally, we demonstrate that hybridising the machine learning-based variable ordering methods with traditional domain-based methods is beneficial.
An Efficient Merge Search Matheuristic for Maximising the Net Present Value of Project Schedules
This paper presents a novel matheuristic framework designed for resource constrained project scheduling, Merge search, which is a variable partitioning and merging mechanism to formulate restricted mixed integer programs with the aim of improving an existing pool of solutions.
Instance Space Analysis for the Car Sequencing Problem
We investigate an important research question for solving the car sequencing problem, that is, which characteristics make an instance hard to solve?
Boosting Ant Colony Optimization via Solution Prediction and Machine Learning
In the first phase of our ML-ACO algorithm, an ML model is trained using a set of small problem instances where the optimal solution is known.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
