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中国管理科学 ›› 2016, Vol. 24 ›› Issue (5): 127-138.doi: 10.16381/j.cnki.issn1003-207x.2016.05.015

• 论文 • 上一篇    下一篇

大数据环境下双层分布式融合决策方法

杜元伟1, 杨娜2   

  1. 1. 中国海洋大学管理学院, 山东 青岛 266100;
    2. 昆明理工大学管理与经济学院, 云南 昆明 650093
  • 收稿日期:2014-04-30 修回日期:2015-05-06 出版日期:2016-05-20 发布日期:2016-05-24
  • 通讯作者: 杜元伟(1981-),男(汉族),吉林白山人,中国海洋大学管理学院教授,博士生导师,研究方向:管理决策、信息融合,E-mail:duyuanwei@ouc.edu.cn. E-mail:duyuanwei@ouc.edu.cn
  • 基金资助:

    国家自然科学基金资助项目(71462022, 71261011);云南省应用基础研究计划资助项目(2013FB030)

Double-layer Distributed Fusion Decision Method in Big Data Environment

DU Yuan-wei1, YANG Na2   

  1. 1. School of Management, Ocean University of China, Qingdao 266100, China;
    2. Faculty of Management and Economics, Kunming University of Science and Technology, Kunming 650093, China
  • Received:2014-04-30 Revised:2015-05-06 Online:2016-05-20 Published:2016-05-24

摘要: 为了解决大数据环境下双层分布式决策中存在的决策推理难题和信息冗余难题,基于该类决策中存在的参与主体庞杂性和业务关系交叉性分析给出了有关推断信息之间存在相关性的假设,并结合证据理论中的基本概率分配函数提出了具有柔性表达优势的推断信息描述机理,在此基础上分别针对上下两层部门构建了能够剔除管理者影响、上层部门影响且可以对部门内部所有决策主体的元推断信息进行科学融合的定理和推论,最后按照"由上至下"的决策秩序构建了大数据环境下双层分布式融合决策的方法步骤。数值对比分析结果表明提出方法具有科学性和可行性,有利于拓展大数据环境下组织管理决策问题的解决思路,探索处理不完备性数据、相关性数据的"大"模式。

关键词: 大数据环境, 双层决策, 分布式决策, 证据理论, 信息融合

Abstract: In order to solve the decision inference problem and the information redundancy problem in double-layer distributed decision in big data environment, a hypothesis that there exits correlation in inference information is made based on the analysis of the complexity of the participating subjects and the overlapping of business relations in such decision, and an inference information description mechanism with the advantage of soft expression is suggested by employing the BPA function in evidence theory. On the ground of that, theorems and inferences are constructed for upper and lower departments to eliminate the influences of both administrators and upper departments and used to make a scientific fusion of all the decision subjects' meta-inference information. Finally, the procedures of double-layer distributed decision in big data environment are constructed according to the "upper to lower" decision order. The result of numerical comparison analysis shows the present method is scientific and feasible. The present method is benefit to develop the thought for solving management decision problems in big data environment and explore the "big" mode for dealing with incompleteness data or correlation data.

Key words: big data environment, double-layer decision, distributed decision, evidence theory, information fusion

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