Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation

Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation
Title:
Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation
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Twenty-Fourth International Joint Conference on Artificial Intelligence
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Publication Date:
26 July 2015
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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.
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