Proceedings Abstracts of the Twenty-Fourth International Joint Conference on Artificial Intelligence

Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation / 418
Minh Luan Nguyen, Siu Cheung Hui, Alvis C. M. Fong

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.