Computer Engineering and Applications ›› 2022, Vol. 58 ›› Issue (12): 304-309.DOI: 10.3778/j.issn.1002-8331.2012-0202

• Engineering and Applications • Previous Articles     Next Articles

Method for Two-Sided Matching About Personal-Job Based on Multiple Criteria Considering Intuitionistic Fuzzy

LI Song, YUAN Anqi   

  1. 1.School of Management, Hebei University, Baoding, Hebei 071002, China
    2.School of Economics and Management, Jiangxi Arts & Ceramic Technology Institute, Jingdezhen, Jiangxi 333000, China
  • Online:2022-06-15 Published:2022-06-15

考虑直觉模糊的多指标人岗双边匹配决策方法

李松,袁安琪   

  1. 1.河北大学 管理学院,河北 保定 071002
    2.江西陶瓷工艺美术职业技术学院 经济管理学院,江西 景德镇 333000

Abstract: According to the character of two-sided matching problem between personal and job in real life, the two-sided matching model about personal-job with multiple attributes and different kinds of information is constructed and a corresponding decision method is proposed based on the intuitionistic fuzzy theory. Firstly, preference information of agents on both sides are transformed into matching satisfaction degree by developing the calculating rules of matching satisfaction degree. Secondly, the satisfaction matrix of both sides are constructed by aggregating perception matrices for all criteria. Further, a two-sided matching model about personal-job with multi-objective optimization is developed to maximize the sum of satisfaction degree of each side under the constraint that they are above the lowest acceptable level of the other side. Finally, an example of personal-job matching problem is given to demonstrate the effectiveness of the two-sided matching method.

Key words: multiple criteria two-sided matching, matching satisfaction degree, intuitionistic fuzzy preference, optimization model

摘要: 针对现实生活中人岗双边匹配决策问题的特点,基于直觉模糊理论,构建了一种具有不同信息类型的人岗双向选择的多指标评价双边匹配决策模型,并提出了相应的决策方法。通过构造人岗双方匹配满意度计算规则,将包含直觉模糊偏好信息的人岗双边主体评价信息转化为匹配满意度;通过对所有标准下的满意度矩阵的集结,构造人岗双方的满意度矩阵。在此基础上,以人岗双方主体可接受最低水平为约束,构建了一个使双方主体满意度最大为目标的人岗双边匹配多目标决策优化模型。通过一个人岗双边匹配问题的案例证明了该方法的合理性。

关键词: 多指标双边匹配, 匹配满意度, 直觉模糊偏好, 优化模型