Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 418-423.
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.
@inproceedings{ijcai2015p65,
title = {Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation},
author = {Nguyen, Minh Luan and Hui, Siu Cheung and Fong, Alvis Cheuk M.},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {418--423},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/65},
}
TY - CPAPER TI - Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation AU - Nguyen, Minh Luan AU - Hui, Siu Cheung AU - Fong, Alvis Cheuk M. T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 418 EP - 423 UR - https://ijcai.org/proceedings/2015/65 ER -Copied
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