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机构地区:[1]哈尔滨工程大学经济管理学院,哈尔滨150001 [2]哈尔滨工业大学计算机科学与技术学院,哈尔滨150001 [3]哈尔滨工程大学理学院,哈尔滨150001
出 处:《统计与决策》2017年第10期47-50,共4页Statistics & Decision
基 金:国家自然科学基金资助项目(71101034);工业和信息化部科研资助项目(G14612001-03)
摘 要:文章针对语言变量评价的风险型群决策问题,提出一种基于云模型、前景理论的风险型多属性群决策方法。该方法通过云模型、前景理论将语言变量评价转换成云前景决策矩阵,并以此计算前景值贴近度确定决策者权重,通过指数映射保证个体云前景决策矩阵在MWA算子下有效集结成群体云前景决策矩阵,结合自修正过程达到一致性要求,最后采用离差最大化规划求解各属性权重并计算各方案的综合排序情况。算例分析验证了上述方法的可行性和有效性。Aiming at the risky linguistic variable group decision-making, this paper proposes a risky multi-attribute group decision-making approach based on the combination of cloud model and prospect theory. In this method, cloud model and prospect model are used to transform the linguistic variable assessment to cloud prospect value decision-making matrix. After that, the weight of decision makers are determined by calculating the prospect value closeness degree. And then the exponential mapping is used to ensure that the individual cloud prospect decision matrix can aggregate effectively to group decision matrix under MWA operator. By combining with the self-modified process, the consistency requirements is reached. Finally, the criteria weights are attained by a programming model which satisfies the algorithm of maximizing deviation, and the order of alternatives can be listed by comparing the prospect value of each alternative. Analyses of examples verify the feasibility and validation of the above method.
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