In this paper, a new decision making approach is proposed for the multi-attribute large group emergency decision-making problem that attribute weights are unknown and expert preference information is expressed by generalized interval-valued trapezoidal fuzzy numbers （GITFNs）. Firstly, a degree of similarity formula between GITFNs is presented. Secondly, expert preference information on different alternatives is clustered into several aggregations via the fuzzy clustering method. As the clustering proceeds, an index of group preference consistency is introduced to ensure the clustering effect, and then the group preference information on different alternatives is obtained. Thirdly, the TOPSIS method is used to rank the alternatives. Finally, an example is taken to show the feasibility and effectiveness of this approach. These method can ensure the consistency degree of group preference, thus decision efficiency of emergency response activities can be improved.
The problem of measuring conflict in large-group decision making is examined with every decision preference expressed by multiple interval intuitionistic trapezoidal fuzzy numbers （IITFNs）. First, a distance measurement between two IITFNs is given and a function of conflict between two members of the large group is proposed. Second, members of the large group are clustered. A measurement model of group conflict, which is applied to aggregating large-group preferences, is then proposed by employing the conflict measure of clusters. Finally, a simulation example is presented to validate the models. These models can deal with the preference analysis and coordination of a large-group decision, and are thus applicable to emergency group decision making.
碳排放依赖型企业在引入嵌入式低碳服务（embedded low-carbonservice）时往往面临着低碳节能水平信息不对称带来的项目风险.鉴于此,在低碳经济背景下,本文考虑了低碳服务商（lowcarbon service provider）的投资水平和低碳节能能力不可观测情形嵌入式低碳服参与主体间最优激励契约的设计问题.同时对该情形下的最优激励契约进行了分析.应用嵌入度刻画嵌入式低碳服务参与主体间的价值共同度,分析了嵌入度对最优激励契约的影响.研究表明,低水平的嵌入度将使得低碳服务商承担更大的项目风险,同时形成需要低碳服务商每期预付节能保证金的合同模式.高水平的嵌入度能促进嵌入式低碳服务的低碳减排效率.
