Athanor: High-Level Local Search Over Abstract Constraint Specifications in Essence
Authors: Saad Attieh, Nguyen Dang, Christopher Jefferson, Ian Miguel, Peter Nightingale
IJCAI 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | A series of case studies show the performance of ATHANOR, benchmarked against several local search solvers on a range of problem classes. |
| Researcher Affiliation | Academia | 1School of Computer Science, University of St Andrews, UK 2Department of Computer Science, University of York, UK |
| Pseudocode | Yes | Algorithm 1 presents the entire search procedure used in the current version of ATHANOR. |
| Open Source Code | Yes | Source code and all data used in this work are publicly available as a github repository 1. 1https://github.com/athanor |
| Open Datasets | Yes | The instances used in this work come from popular benchmarking datasets whenever possible, and are randomly generated otherwise. The instances for TSP, CVRP, Knapsack and Social Golfers are taken from TSPLIB [Reinelt, 1995], VRP-REP [Mendoza et al., 2014], Pisinger s hard knapsack [Pisinger, 2005], and CSPLib [Miguel et al., 2000], respectively. All instances or reference links to them are available in the github repository of ATHANOR6. |
| Dataset Splits | No | The paper evaluates solvers on problem instances but does not describe training, validation, or test splits for datasets, as it focuses on solving constraint programming problems rather than machine learning model training. |
| Hardware Specification | No | The paper mentions using a 'Cirrus UK National Tier-2 HPC Service at EPCC', but this is a general service name and does not provide specific details such as GPU/CPU models or memory. |
| Software Dependencies | Yes | The Mini Zinc backend of SAVILE ROW along with Mini Zinc 2.1.7 [Nethercote et al., 2007] were used to produce Flat Zinc inputs for Chuffed, Oscar-CBLS and Yuck. |
| Experiment Setup | Yes | For each problem class, all solvers were run ten times (except Chuffed, as it is deterministic). For optimisation problems... the best objective found by each solver is logged every second. ...I 10, Z 1.3, L 500 algorithm constants. |