属性权重完全未知的犹豫模糊双边匹配决策

doi:10.11772/j.issn.1001-9081.2016.08.2268

计算机应用 ›› 2016, Vol. 36 ›› Issue (8): 2268-2273.DOI: 10.11772/j.issn.1001-9081.2016.08.2268

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

收稿日期:2015-12-10 修回日期:2016-03-14 出版日期:2016-08-10 发布日期:2016-08-10
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）。

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).

摘要/Abstract

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

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

中图分类号:

TP181

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.

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.

参考文献

[1] GALE D,SHAPLEY L S.College admissions and the stability of marriage[J].American Mathematical Monthly,1962,69(1):9-15.
[2] 乐琦.无差异区间型多指标匹配决策方法[J].系统工程学报,2014,29(1):41-47.(YUE Q.Indifference interval multiple criteria matching decision method[J].Journal of Systems Engineering,2014,29(1):41-47.)
[3] ROTH A E.Common and conflicting interests in two-sided matching markets[J].European Economic Review,1985,27(1):75-96.
[4] ELITZUR R,GAVIOUS A.A multi-period game theoretic model of venture capitalists and entrepreneurs[J].European Journal of Operational Research,2003,144(2):440-453.
[5] 万树平,李登峰.具有不同类型信息的风险投资商与投资企业多指标双边匹配决策方法[J].中国管理科学,2014,22(2):40-47.(WAN S H,LI D F.Decision making method for multi-attribute two-sided matching problem between venture capitalists and investment enterprises with different kinds of information[J].Chinese Journal of Management Science,2014,22(2):40-47.)
[6] 梁海明,姜艳萍.二手房组合交易匹配决策方法[J].系统工程理论与实践,2015,35(2):358-367.(LIANG H M,JIANG Y P.Decision-making method on second-hand house combination matching[J].Systems Engineering-Theory&Practice,2015,35(2):358-367.)
[7] 谈群,彭黎,李志猛,等.一种航天侦察任务-资源匹配的负载均衡方法[J].国防科技大学学报,2011,33(2):95-99.(TAN Q,PENG L,LI Z M,et al.A load balancing method for matching reconnaissance tasks and satellite resources[J].Journal of National University of Defense Technology,2011,33(2):95-99.)
[8] 林杨,王应明.基于感知效用的多阶段多属性匹配决策途径[J].计算机应用,2015,35(6):1628-1632.(LIN Y,WANG Y M.Approach for multi-period multi-attribute matching decision making based on perceived expectation[J].Journal of Computer Applications,2015,35(6):1628-1632.)
[9] 陈圣群,王应明,施海柳.多属性匹配决策的等级置信度融合法[J].系统工程学报,2015,30(1):25-33.(CHEN S Q,WANG Y M,SHI H L.Rank belief degrees fusion method for multi-attribute matching decision making[J].Journal of Systems Engineering,2015,30(1):25-33.)
[10] JIANG Z Z,IP W H,LAU H C,et al.Multi-objective optimization matching for one-shot multi-attribute exchanges with quantity discounts in E-brokerage[J].Expert Systems with Applications,2011,38(4):4169-4180.
[11] ZHANG Z,GUO C H.A hybrid multiple attributes two-sided matching decision making method with incomplete weight information[C]//BI'11 Proceedings of the 2011 International Conference on Brain Informatics,LNCS 6889.Berlin:Springer,2011:272-283.
[12] 徐泽水.不确定多属性决策方法及应用[M].北京:清华大学出版社,2004:12-20.(XU Z S.Uncertain Multiple Attribute Decision Making:Methods and Applications[M].Beijing:Tsinghua University Press,2004:12-20.)
[13] XIA M,XU Z S.Hesitant fuzzy information aggregation in decision making[J].International Journal of Approximate Reasoning,2011,52(3):395-407.
[14] 王坚强,吴佳亭.基于优序关系的犹豫模糊语言多准则决策方法[J].控制与决策,2015,30(5):887-891.(WANG J Q,WU J T.Method for multi-criteria decision making with hesitant fuzzy linguistic based on outranking relation[J].Control and Decision,2015,30(5):887-891.)
[15] TORRA V.Hesitant fuzzy sets[J].International Journal of Intelligent Systems,2010,25(6):529-539.
[16] XIA M,XU Z,CHEN N.Some hesitant fuzzy aggregation operators with their application in group decision making[J].Group Decision and Negotiation,2013,22(2):259-279.
[17] XU Z,ZHANG X.Hesitant fuzzy multi-attribute decision making based on TOPSIS with incomplete weight information[J],Knowledge-Based Systems,2013,52:53-64.
[18] 樊治平,乐琦.基于完全偏好序信息的严格双边匹配方法[J].管理科学学报,2014,17(1):21-34.(FAN Z P,YUE Q.Strict two-sided matching method based on complete preference ordinal information[J].Journal of Management Sciences in China,2014.17(1):21-34.)
[19] KASPERSKI A,ZIELINSKI P.On combinatorial optimization problems on matroids with uncertain weights[J].European Journal of Operational Research,2007,177(2):851-864.
[20] 王应明.运用离差最大化方法进行多指标决策与排序[J].系统工程与电子技术,1998,20(7):24-26.(WANG Y M.Using the method of maximizing deviations to make decision for multiindicies[J].Systems Engineering and Electronics,1998,20(7):24-26.)
[21] DE LEEUW J,PRUZANSKY S.A new computational method to fit the weighted Euclidean distance model[J].Psychometrika,1978,43(4):479-490.
[22] 樊治平,李铭洋.考虑稳定匹配条件的双边满意匹配决策方法[J].中国管理科学,2009.22(4):113-118.(FAN Z P,LI M Y.Decision analysis method for two-sided satisfied matching considering stable matching condition[J].Chinese Journal of Management Science,2009,22(4):113-118.)
[23] LI D F,WAN S P.Fuzzy linear programming approach to multiattribute decision making with multiple types of attribute values and incomplete weight information[J].Applied Soft Computing,2013,13(11):4333-4348.
[24] CHEN N,XU Z,XIA M M.Interval-valued hesitant preference relations and their applications to group decision making[J].Knowledge-Based Systems,2013,37:528-540.

属性权重完全未知的犹豫模糊双边匹配决策

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

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