Lin Hui, Wang Zhou-Jing
School of Information, Zhejiang University of Finance and Economics, Hangzhou 310018, China.
Int J Environ Res Public Health. 2017 Sep 17;14(9):1078. doi: 10.3390/ijerph14091078.
Low-carbon tourism plays an important role in carbon emission reduction and environmental protection. Low-carbon tourism destination selection often involves multiple conflicting and incommensurate attributes or criteria and can be modelled as a multi-attribute decision-making problem. This paper develops a framework to solve multi-attribute group decision-making problems, where attribute evaluation values are provided as linguistic terms and the attribute weight information is incomplete. In order to obtain a group risk preference captured by a linguistic term set with triangular fuzzy semantic information, a nonlinear programming model is established on the basis of individual risk preferences. We first convert individual linguistic-term-based decision matrices to their respective triangular fuzzy decision matrices, which are then aggregated into a group triangular fuzzy decision matrix. Based on this group decision matrix and the incomplete attribute weight information, a linear program is developed to find an optimal attribute weight vector. A detailed procedure is devised for tackling linguistic multi-attribute group decision making problems. A low-carbon tourism destination selection case study is offered to illustrate how to use the developed group decision-making model in practice.
低碳旅游在碳排放减少和环境保护中发挥着重要作用。低碳旅游目的地的选择通常涉及多个相互冲突且不可通约的属性或标准，可将其建模为多属性决策问题。本文提出了一个框架来解决多属性群体决策问题，其中属性评估值以语言术语给出，且属性权重信息不完整。为了获得由具有三角模糊语义信息的语言术语集所捕捉的群体风险偏好，在个体风险偏好的基础上建立了一个非线性规划模型。我们首先将基于个体语言术语的决策矩阵转换为各自的三角模糊决策矩阵，然后将它们聚合为一个群体三角模糊决策矩阵。基于这个群体决策矩阵和不完整的属性权重信息，开发了一个线性规划来找到最优属性权重向量。设计了一个详细的程序来处理语言多属性群体决策问题。提供了一个低碳旅游目的地选择的案例研究，以说明如何在实践中使用所开发的群体决策模型。
