Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation
Abstract
Parallel Test Paper Generation (k-TPG) is a biobjective distributed resource allocation problem, which aims to generate multiple similarly optimal test papers automatically according to multiple user-specified criteria. Generating high-quality parallel test papers is challenging due to its NP-hardness in maximizing the collective objective functions. In this paper, we propose a Collective Biobjective Optimization (CBO) algorithm for solving k-TPG. CBO is a multi-step greedy-based approximation algorithm, which exploits the submodular property for biobjective optimization of k-TPG.Experiment results have shown that CBO has drastically outperformed the current techniques in terms of paper quality and runtime efficiency.
Cite
Text
Nguyen et al. "Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation." International Joint Conference on Artificial Intelligence, 2015.Markdown
[Nguyen et al. "Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation." International Joint Conference on Artificial Intelligence, 2015.](https://mlanthology.org/ijcai/2015/nguyen2015ijcai-collective/)BibTeX
@inproceedings{nguyen2015ijcai-collective,
title = {{Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation}},
author = {Nguyen, Minh Luan and Hui, Siu Cheung and Fong, Alvis Cheuk Ming},
booktitle = {International Joint Conference on Artificial Intelligence},
year = {2015},
pages = {418-424},
url = {https://mlanthology.org/ijcai/2015/nguyen2015ijcai-collective/}
}