The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/17081021

Floris Doolaard; Yorke-Smith, Neil (2022): Online COP heuristic learning code: "Online Learning of Variable Ordering Heuristics for Constraint Optimisation Problems". Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/17081021.v1

Software

• Artificial Intelligence and Image Processing

constraint optimisation problem, Gecode, machine learning, random forest regression, source code, variable ordering

BSD-3-Clause

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Floris Doolaard, Neil Yorke-Smith

This repository contains the source code for the algorithm designed to learn on-the-fly (variable ordering) heuristics for constraint optimization problems (COPs). To apply heuristics to COPs the Geocde solver is used and adapted.

The corresponding paper is:

Online Learning of Variable Ordering Heuristics for Constraint Optimisation Problems

Floris Doolaard and Neil Yorke‐Smith

Annals of Mathematics and Artificial Intelligence

https://doi.org/10.1007/s10472-022-09816-z

published online 2022

• 2022-11-24 first online, published, posted

4TU.ResearchData

Python, C++, MiniZinc

Online Learning of Variable Ordering Heuristics for Constraint Optimisation Problems

• Foundations of Trustworthy AI - Integrating Reasoning, Learning and Optimization (grant code 952215) [more info...] European Commission

TU Delft, Faculty of Electrical Engineering, Mathematics and Computer Science