A Hybrid Evolutionary Algorithm for the Diversified Top-K Weight Clique Search Problem (Student Abstract)
Abstract
The diversified top-k weight clique (DTKWC) search problem is an important generalization of the diversified top-k clique search problem, which extends the DTKC search problem by taking into account the weight of vertices. This problem involves finding at most k maximal weighted cliques that cover maximum weight of vertices with low overlapping in a given graph. In this study, a mixed integer linear program constraint formulation is proposed to model DTKWC search problem and an efficient hybrid evolutionary algorithm (HEA-D) based on some heuristic strategies is proposed to tackle it. Experiments on two sets of 110 graphs show that HEA-D outperforms the state-of-art methods.
Cite
Text
Wu and Yin. "A Hybrid Evolutionary Algorithm for the Diversified Top-K Weight Clique Search Problem (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21678Markdown
[Wu and Yin. "A Hybrid Evolutionary Algorithm for the Diversified Top-K Weight Clique Search Problem (Student Abstract)." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/wu2022aaai-hybrid/) doi:10.1609/AAAI.V36I11.21678BibTeX
@inproceedings{wu2022aaai-hybrid,
title = {{A Hybrid Evolutionary Algorithm for the Diversified Top-K Weight Clique Search Problem (Student Abstract)}},
author = {Wu, Jun and Yin, Minghao},
booktitle = {AAAI Conference on Artificial Intelligence},
year = {2022},
pages = {13083-13084},
doi = {10.1609/AAAI.V36I11.21678},
url = {https://mlanthology.org/aaai/2022/wu2022aaai-hybrid/}
}