基于直觉模糊集的公私合营项目方案选择
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  • 英文篇名:Framework for Selection of PPP Project Scheme Based on Intuitionistic Fuzzy Sets
  • 作者:商克俭 ; 冯东 ; 李乃文
  • 英文作者:Shang Kejian;Feng Dongmei;Li Naiwen;School of Business Administration, Liaoning Technical University;
  • 关键词:公私合作模式(PPP模式) ; 方案选择 ; 区间直觉模糊数 ; 模糊测度
  • 英文关键词:public-private partnership(PPP);;plan selection;;interval-valued intuitionistic fuzzy number;;fuzzy measure
  • 中文刊名:TJJC
  • 英文刊名:Statistics & Decision
  • 机构:辽宁工程技术大学工商管理学院;
  • 出版日期:2019-02-18 13:37
  • 出版单位:统计与决策
  • 年:2019
  • 期:v.35;No.519
  • 基金:国家自然科学基金资助项目(71201012);; 辽宁省社会科学规划基金项目(L15BSZ023;L14CZY046);; 辽宁省哲学社会科学规划基金项目(L16CGL012)
  • 语种:中文;
  • 页:TJJC201903043
  • 页数:4
  • CN:03
  • ISSN:42-1009/C
  • 分类号:180-183
摘要
项目方案的选择是PPP项目研究中的棘手难题。文章用区间直觉模糊数代替实数,以减少信息的损失,而后采用模糊测度代替权重以表示评价指标的重要性,并基于区间直觉模糊Choquet积分算子构建基于直觉模糊集和模糊测度的多属性决策方法来实现PPP方案的最优选择。最后通过实例分析验证了模型的有效性。
        The project scheme targets the difficult problem in PPP project research. This paper uses interval intuitionistic fuzzy number as a substitute of real number to reduce the loss of information and then uses fuzzy measure instead of weight to express the importance of evaluation index. Based on the interval intuitionistic fuzzy Choquet integral operator, a multi-attribute decision making method based on intuitionistic fuzzy set and fuzzy measure is constructed to realize the optimal choice of PPP scheme. Finally, the effectiveness of the proposed model is verified by a case study. The paper effectively solves the problem of information loss and the independence between evaluation indexes in project program decision making, which greatly improves the rationality and scientificity of decision making,and provides a reference for project decision makers in program selection.
引文
[1]陈婷婷,宋永发.AHP-TOPSIS法在地铁车站方案选择中的应用[J].地下空间与工程学报,2013,9(2).
    [2]田林钢,靳聪聪.基于改进的熵权-TOPSIS法的震损水库最佳除险加固方案选择[J].水电能源科学,2013,31(9).
    [3]Atanassov K,Gargov G.Interval Valued Intuitionistic Fuzzy Sets[J].Fuzzy Sets Syst,1989,(31).
    [4]Sugeno M.Fuzzy Measures and Fuzzy Integrals[J].Fuzzy Automata and Decision Processes.1977,78(33).

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