计算机应用 ›› 2015, Vol. 35 ›› Issue (6): 1628-1632.DOI: 10.11772/j.issn.1001-9081.2015.06.1628

• 人工智能 • 上一篇    下一篇

基于感知效用的多阶段多属性匹配决策途径

林杨1,2, 王应明2   

  1. 1. 福建师范大学 经济学院, 福州 350108;
    2. 福州大学 经济与与管理学院, 福州 350116
  • 收稿日期:2015-01-31 修回日期:2015-04-07 发布日期:2015-06-12
  • 通讯作者: 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、实验经济学;linyang42@163.com
  • 作者简介:王应明(1964-),男,江苏海安人,教授,博士,主要研究方向:决策理论与方法、数据包络分析。
  • 基金资助:

    国家自然科学基金资助项目(71371053);国家杰出青年科学基金资助项目(70925004);福建师范大学青年教师成长基金资助项目(VH-059)。

Approach for multi-period and multi-attribute matching decision based on perceived expectation

LIN Yang1,2, WANG Yingming2   

  1. 1. School of Economics, Fujian Normal University, Fuzhou Fujian 350108, China;
    2. School of Economics and Management, Fuzhou University, Fuzhou Fujian 350116, China
  • Received:2015-01-31 Revised:2015-04-07 Published:2015-06-12

摘要:

针对当前双边匹配研究仅限于单阶段情形,提出一种多阶段多属性情形下的匹配决策方法。 首先,根据主体给出的各阶段orness测度,建立以各阶段orness测度与所求的累积权重orness测度间的偏差和,以及各累积权重之间的最大离差,两者之和最小为准则计算得到匹配对象各属性的累积权重。然后,与专家给出的属性值加权集结得到其累积评价值,进而依据逼近理想解法的思想测算匹配对象的累积评价值与主体期望的正负理想值之间的吻合度,得到主体的感知效用并作为匹配依据。通过建立一种基于感知效用的双目标优化模型,使用极大极小法求解该模型获得匹配结果。最后,通过一个算例比较极大极小法与线性加权法,前者得到的双方损益效用差值(0.33)小于后者(0.36);另外,所提方法使较劣一方的损益效用达到最大。

关键词: 多属性匹配决策, 多阶段, orness测度, 累积权重, 感知效用, 极大极小法

Abstract:

The current research of bilateral matching problem is limited to single-period scenario. Aiming at the issue, an approach was proposed to study matching decision problem under multi-period and multi-attribute. First, through the orness, a measurement of Agent's preference, an optimal program was constructed to determine the cumulative weight of an Agent within each attribute. More specifically, the criteria of this program consisted of two parts: one part was to minimize the sum of deviation between an orness and corresponding cumulative weight of an Agent in different period; another part was to minimize the maximum disparity among cumulative weights of an Agent. Then, based on obtained cumulative weight, matching degree which represented by Agent's positive and negative ideal between the cumulative evaluation value and perceived expectation can be determined via the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). Furthermore, a double-objective optimization model based on perceived expectation was constructed and the minimax method was used to solve this model for obtaining matching results. Finally, a numerical example was given to compare the minimax method with the linear weighting method. The results show that difference of profit and loss of utility obtained by the former method was 0.33, less than 0.36 that obtained by the latter method. Moreover, it also demonstrates the proposed method can maximize the profit and loss of utility of inferior side.

Key words: multi-attribute matching decision, multi-period, orness measurement, cumulative weight, perceived expectation, minimax method

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