Approach for hesitant fuzzy two-sided matching decision making under unknown attribute weights

doi:10.11772/j.issn.1001-9081.2016.08.2268

Journal of Computer Applications ›› 2016, Vol. 36 ›› Issue (8): 2268-2273.DOI: 10.11772/j.issn.1001-9081.2016.08.2268

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Approach for hesitant fuzzy two-sided matching decision making under unknown attribute weights

LIN Yang^1,2, LI Yuansheng¹, WANG Yingming²

1. School of Economics, Fujian Normal University, Fuzhou Fujian 350117, China;
2. Institute of Decision Science, Fuzhou University, Fuzhou Fujian 350117, China

Received:2015-12-10 Revised:2016-03-14 Online:2016-08-10 Published:2016-08-10
Supported by:
This work is partially supported by the National Natural Science Foundation of China (70925004), the Social Science Foundation of Fujian Province (FJ2015C111), the Teaching Reform of Undergraduate Project of Fujian Normal University (I201501002).

属性权重完全未知的犹豫模糊双边匹配决策

林杨^1,2, 黎元生¹, 王应明²

1. 福建师范大学经济学院, 福州 350117;
2. 福州大学决策科学研究所, 福州 350117

通讯作者: 黎元生
作者简介:林杨(1983-),男,福建福州人,实验师,博士研究生,主要研究方向:最优化理论、决策分析;黎元生(1974-),男,福建上杭人,教授,博士,主要研究方向:经济统计学;王应明(1964-),男,江苏海安人,教授,博士,主要研究方向:决策分析、数据包络分析。
基金资助:
国家自然科学基金资助项目（70925004）；福建省社科规划青年项目（FJ2015C111）；福建师范大学本科教学改革研究项目（I201501002）。

Abstract

Abstract: To deal with Two-Sided Matching (TSM) problem based on Hesitant Fuzzy Value (HFV) of unknown weights, a multi-attribute matching decision making approach was proposed. To begin with, the weight information was determined by maximizing the sum of deviations of the given values in terms of HFVs with multi-attribute evaluated by both two-sided Agents. Then, the matching degree could be aggregated via an operation of adjusted hesitant fuzzy weighted averaging with obtained weights and multi-attribute information. In addition, a multi-objective optimization model was established based on the matching degree of two sides. By solving this model into single objective optimization model in min-max method, the matching scheme was generated. Finally, a numerical illustration and comparison was taken, the solutions of objectives by the proposed method were respectively 1.689 and 1.575, and a unique matching scheme was obtained. The experimental results show that the proposed method can avoid multiple solutions caused by subjective weights of goal functions.

Key words: matching decision making, hesitant fuzzy set, multiattribute deviation, weight, min-max method

摘要： 针对基于犹豫模糊属性（HFV）信息且权重完全未知的双边匹配（TSM）问题，提出一种多属性匹配决策方法。首先，根据双方主体给出的犹豫模糊多属性评价值，通过最大化各属性之间的离差和从而确定属性权重；然后，由犹豫模糊有序加权平均算子集结多属性及权重信息获得双方的匹配度；进而建立一种基于匹配度的多目标优化模型，并使用极大极小法转化为单目标优化模型求解得到匹配方案；最后，进行实例分析和对比，所提方法得到目标函数值分别为1.689和1.575，且匹配解唯一。实验结果表明，所提方法可避免因主观确定目标函数权重而产生不唯一匹配解。

关键词: 匹配决策, 犹豫模糊集, 多属性离差, 权重, 极大极小法

CLC Number:

TP181

LIN Yang, LI Yuansheng, WANG Yingming. Approach for hesitant fuzzy two-sided matching decision making under unknown attribute weights[J]. Journal of Computer Applications, 2016, 36(8): 2268-2273.

林杨, 黎元生, 王应明. 属性权重完全未知的犹豫模糊双边匹配决策[J]. 计算机应用, 2016, 36(8): 2268-2273.

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Approach for hesitant fuzzy two-sided matching decision making under unknown attribute weights

属性权重完全未知的犹豫模糊双边匹配决策

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