---
title: "Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation"
authors:
  - "Minh Luan Nguyen"
  - "Siu Cheung Hui"
  - "Alvis Cheuk M. Fong"
doi: ""
url: "https://ijcai.org/proceedings/2015/65"
pdf: "https://ijcai.org/proceedings/2015/0065.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "418-423"
track: "Main Track"
keywords:
---

# Collective Biobjective Optimization Algorithm for Parallel Test Paper Generation

Minh Luan Nguyen, Siu Cheung Hui, Alvis Cheuk M. Fong

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, 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.