基于语言值格蕴涵代数的偏好顺序结构评估决策方法

针对具有可比性和不可比性语言值信息的决策问题,提出基于语言值格蕴涵代数(L_V(n×2))的多属性决策方法.讨论L_(n×2)上的语言值评价矩阵及其性质,提出L_V(n×2)上的优先函数和格值程度差,充分考虑属性值差距信息,将格值程度差应用到择优排序上.通过语言值向量,建立语言值向量合成矩阵,处理决策问题中的多专家多属性信息.引入语言值评价矩阵加权聚合算子对语言值评价矩阵进行聚合,利用偏好顺序结构评估(PROMETHEE)决策方法的非补偿性,构建基于语言值格蕴涵代数的PROMETHEE决策模型,并通过网络商品评价实例说明文中方法的有效性和实用性.     

Double parameters TOPSIS for multi-attribute linguistic group decision making based on the intuitionistic Z-linguistic variables

Multi-attribute linguistic group decision making (MALGDM) is one of the most widespread and important human activities. Therefore, it is extremely significant to study the efficient methods to address linguistic information. Extended by classical fuzzy number, Z-number can describe both restraints and reliability, which has more capacity to represent human knowledge. In this paper, we will propose the intuitionistic Z-linguistic set (IZLS) combined the intuitionistic uncertain linguistic set (IULS) with Z-number. We further introduce the operational rules, new score and accuracy functions of it. Then, the Minkowski distance between two intuitionistic Z-linguistic variables is proposed with the attribute’s weight obtained by the priority relationship among different categories. Finally, we propose an extended TOPSIS method with double parameters which consider both preference of alternatives and optimism of decision makers (DMs). Case study on investment strategy and medical diagnosis are presented to show the applicability of the proposed approach and some comparisons are conducted to illustrate its superiorities.     

面向大群体用户的模糊服务选择

面向群体的服务选择在社会生活中应用非常广泛;而群体规模较大并且QoS需求个性化和模糊QoS给Web服务选择带来巨大困难。基于多属性群决策理论提出面向大群体用户的模糊服务选择(BGFWSS),其包括5个步骤:群体偏好确定、族加权权重确定、构造族加权规格化决策矩阵、确定理想方案、群体综合评价。另外,还介绍了一个新的Web服务QoS模型,其能够描述实数、区间数、直觉模糊数表示的QoS信息。实验数据表明,BGFWSS能够很好地解决模糊QoS的大规模群体用户的服务选择问题。     

A possibility degree method for interval-valued intuitionistic fuzzy multi-attribute group decision making

The ranking of interval-valued intuitionistic fuzzy sets (IVIFSs) is very important for the interval-valued intuitionistic fuzzy decision making. From the probability viewpoint, the possibility degree of comparison between two interval-valued intuitionistic fuzzy numbers (IVIFNs) is defined by using the notion of 2-dimensional random vector, and a new method is then developed to rank IVIFNs. Hereby the ordered weighted average operator and hybrid weighted average operator for IVIFNs are defined based on the Karnik–Mendel algorithms and employed to solve multi-attribute group decision making problems with IVIFNs. The individual overall attribute values of alternatives are obtained by using the weighted average operator for IVIFNs. By using the hybrid weighted average operator for IVIFNs, we can obtain the collective overall attribute values of alternatives, which are used to rank the alternatives. A numerical example is examined to illustrate the effectiveness and flexibility of the proposed method in this paper.     

Scheduling with multi-attribute setup times

In this paper we address a scheduling problem with multi-attribute setup times originated from the manufacturing plant of a company producing PVC sheets. In the considered scheduling problem, each job has a number of attributes and each attribute has one or more levels. Because there is at least one different level of attribute between two adjacent jobs, it is necessary to make a setup adjustment whenever there is a switch to a different job. The objective of the problem is to determine a processing sequence so as to minimize the total setup time on a single machine.     

基于概率犹豫信息集成方法的群决策模型*

现有犹豫模糊集在描述决策信息时会导致决策信息大量损失,因此文中基于概率犹豫模糊信息集成算子,构建多属性群决策模型.首先在概率犹豫模糊环境下引入Archimedean范数,定义概率犹豫模糊运算法则.基于该运算法则,提出广义概率犹豫模糊有序加权平均(GPHFOWA)算子和广义概率犹豫模糊有序加权几何(GPHFOWG)算子,并讨论它们的基本性质.然后分析GPHFOWA算子和GPHFOWG算子的常见形式和相互关系.最后运用提出的2类算子构建概率犹豫模糊多属性群决策模型,并且通过供应商的选择实例验证决策模型的可行性和有效性.     

Application of Seismic Attribute Technique to estimate the 3D model of Hydraulic Flow Units: A case study of a gas field in Iran

One of the most important steps in evaluation and development of hydrocarbon reservoirs is the mapping of their characteristics. Nowadays, Seismic Attribute Technique is used to build parameters of hydrocarbon reservoirs in inter-well spaces. One of these parameters is the Flow Zone Index (FZI) that has a significant effect on different stages of evaluation, completion, primary and secondary production, reservoir modeling and reservoir management. The aim of this study is to introduce an equation using seismic attribute and FZI log in wells and then generalize it to predict FZI throughout the reservoir. For this purpose, acoustic impedance (AI) volume as an external attribute was created while internal attributes were computed from seismic data. After that, The best set of attributes was determined using stepwise regression after which seismic attributes were applied to multi-attribute analysis to predict FZI. Then, the attribute map resulted from multi-attribute analysis was used to interpret the spatial distribution of the gas bearing carbonate layers. Finally, the optimum number of Hydraulic Flow Units (HFU) was determined by analyzing the break point in the plot of cumulative frequency of FZI for wells and was generalized all over the reservoir by using the 3D HFU model. The results demonstrated that multi-attribute analysis was a striking technique for HFU estimation in hydrocarbon reservoirs that reduces cost and increases rate of success in hydrocarbon exploration. Distribution of producible hydrocarbon zones along with the seismic lines around the reservoir was characterized by studying this model which can help us in choosing the location of new wells and more economical drilling operations.     

Multidimensional risk analysis of hydrogen pipelines

Hydrogen has the highest mass specific energy content of all conventional fuels and is the most abundant element in the universe. It is considered as a renewable resource and sustainable solution for reducing global fossil fuel consumption and combating global warming. In general, it must be transported from production plants to demand points. Thus, the delivery process of its supply chain leads to the possibility of there being new forms of hazard. Pipelines have proven to be one of the cheapest ways to transport hydrogen. However, failures in pipelines can pose major risks. In this context, this paper proposes a multicriteria decision model for assessing the risk in hydrogen pipelines. By incorporating the decision maker's preferences structure into the decision process, the model enables sections of the pipeline to be ranked in terms of risk. The model proposed in this work is considered as an evolution of previous studies in the area, due to new features incorporated in the process. Finally, a numerical application is conducted in order to test the model.     

Improved TOPSIS decision model for NPP emergencies

In this paper,an improved decision model is developed for its use as a tool to respond to emergencies at nuclear power plants.Given the complexity of multi-attribute emergency decision-making on nuclear accident,the improved TOPSIS method is used to build a decision-making model that integrates subjective weight and objective weight of each evaluation index.A comparison between the results of this new model and two traditional methods of fuzzy hierarchy analysis method and weighted analysis method demonstrates that the improved TOPSIS model has a better evaluation effect.