Wang Xin-Fan, Wang Jian-Qiang, Deng Sheng-Yue
School of Science, Hunan University of Technology, Zhuzhou 412007, China ; School of Business, Central South University, Changsha 410083, China.
ScientificWorldJournal. 2013 Sep 26;2013:202085. doi: 10.1155/2013/202085. eCollection 2013.
We investigate the dynamic stochastic multicriteria decision making (SMCDM) problems, in which the criterion values take the form of log-normally distributed random variables, and the argument information is collected from different periods. We propose two new geometric aggregation operators, such as the log-normal distribution weighted geometric (LNDWG) operator and the dynamic log-normal distribution weighted geometric (DLNDWG) operator, and develop a method for dynamic SMCDM with log-normally distributed random variables. This method uses the DLNDWG operator and the LNDWG operator to aggregate the log-normally distributed criterion values, utilizes the entropy model of Shannon to generate the time weight vector, and utilizes the expectation values and variances of log-normal distributions to rank the alternatives and select the best one. Finally, an example is given to illustrate the feasibility and effectiveness of this developed method.
我们研究动态随机多准则决策（SMCDM）问题，其中准则值采用对数正态分布随机变量的形式，且论据信息是从不同时期收集的。我们提出了两种新的几何聚合算子，如对数正态分布加权几何（LNDWG）算子和动态对数正态分布加权几何（DLNDWG）算子，并开发了一种用于具有对数正态分布随机变量的动态SMCDM的方法。该方法使用DLNDWG算子和LNDWG算子来聚合对数正态分布的准则值，利用香农熵模型生成时间权重向量，并利用对数正态分布的期望值和方差对备选方案进行排序并选择最佳方案。最后，给出一个例子来说明所开发方法的可行性和有效性。
