Computer Engineering and Applications ›› 2017, Vol. 53 ›› Issue (16): 249-257.DOI: 10.3778/j.issn.1002-8331.1609-0324

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Multi-objective evolutionary based on matrix-coding to solve interview grouping problem

XU Yulong1, SUN Xiaojing2, CAO Li1, WANG Xiaohui1   

  1. 1.Institute of Information and Technology, Henan University of Chinese Medicine, Zhengzhou 450046, China
    2.Branch in Zhengzhou of China Nuclear Power Engineering Co., Ltd, Zhengzhou 450006, China
  • Online:2017-08-15 Published:2017-08-31

基于矩阵编码的多目标进化求解面试分组问题

许玉龙1,孙晓静2,曹  莉1,王晓辉1   

  1. 1.河南中医药大学 信息技术学院,郑州 450046
    2.中国核电工程有限公司郑州分公司 实物保护研究所,郑州 450006

Abstract: The problem of grouping interview and thesis defense belongs to the complex constraint optimization problem, which is often appeared in the enrollment of student in university. In order to research this problem, the internal constraints and restriction relations of this issue are analyzed firstly. In addition, the mathematical model of grouping interview and thesis defense problem is built, and the optimization objective function is established. Then, based on the established mathematical model, the multi-objective evolution with matrix-coding scheme is used to solve this grouping problem. Meanwhile, the conventional method of solving this problem is proposed for comparison. The experimental comparisons show that the multi-objective evolution provides comprehensive performance and greater adaptability than the conventional method.

Key words: multi-objective, grouping interview, matrix encoding, mathematical model

摘要: 面试分组是高校自主招生、毕业答辩中较为常见的实际问题,该问题属于具有限制条件的组合优化类难题。针对该问题,首先分析内部限制条件和制约关系,并建立合适的数学模型,确定优化目标函数。然后采用基于矩阵的多目标进化算法研究此类问题,依据建立的数学模型,构造矩阵染色体编码方式对问题进行求解,同时利用常规的方法求解该问题进行对比。实验结果显示,多目标进化算法求解此类问题时,在解的质量和数量上明显优于常规算法。

关键词: 多目标, 面试分组, 矩阵编码, 数学模型