A Bitwise GAC Algorithm for Alldifferent Constraints

Authors: Zhe Li, Yaohua Wang, Zhanshan Li

IJCAI 2023 | Conference PDF | Archive PDF | Plain Text | LLM Run Details

Reproducibility Variable Result LLM Response
Research Type Experimental Our experiments show that Alldiffbit outperforms the state-of-the-art GAC algorithms over 60%. Our experiments on large numbers of constraint problems (CPs) show that Alldiffbit is both efficient and stable.
Researcher Affiliation Academia 1National University of Defense Technology, Changsha, China 2Jilin University, Changchun, China
Pseudocode Yes Algorithm 1: FIND SCCS
Open Source Code Yes The source code and dataset are available at https://github.com/leezear2022/alldiff-choco.
Open Datasets Yes To conduct a comprehensive evaluation, we used various alldifferent CP instances from the XCSP3 website [Boussemart et al., 2016]4. http://xcsp.org/
Dataset Splits No The paper does not provide specific details about training, validation, or test dataset splits (e.g., percentages, sample counts, or specific splitting methodology).
Hardware Specification Yes Our experiments were conducted on a PC with an AMD Ryzen 9 7950X CPU @ 4.5GHz, 32 GB RAM, and 64-bit Windows 11.
Software Dependencies Yes All the algorithms were implemented in the Java-based CP solver, Choco [Prud homme et al., 2017]5 using Open JDK 19.
Experiment Setup Yes To ensure fairness, We used binary branching search with DOM [Dechter and Meiri, 1994] as the variable ordering heuristic, and min value as the value ordering heuristic.