2-dimension Uncertain Linguistic Variables Research Articles

A method of multiple-attribute group decision making problem for 2-dimension uncertain linguistic variables based on cloud model

A method of multiple-attribute group decision making problem for 2-dimension uncertain linguistic variables based on cloud model

Multi-attribute group decision making method under 2-dimension uncertain linguistic variables

A method is proposed to deal with the uncertain multiple attribute group decision making problems, where 2-dimension uncertain linguistic variables (2DULVs) are used as the reliable way for the experts to express their fuzzy subjective evaluation information. Firstly, in order to measure the 2DULVs more accurately, a new method is proposed to compare two 2DULVs, called a score function, while a new function is defined to measure the distance between two 2DULVs. Secondly, two optimization models are established to determine the weight of experts and attributes based on the new distance formula and a weighted average operator is used to determine the comprehensive evaluation value of each alternative. Then, a score function is used to determine the ranking of the alternatives. Finally, the effectiveness of the proposed method is proved by an illustrated example.

SNA-based multi-criteria evaluation of multiple construction equipment: A case study of loaders selection

Selecting the proper construction equipment is a challenging task owing to a wide range of available types as well as a host of criteria to be considered during decision making. To deal with this, a heterogeneous group decision-making framework to evaluate multiple purchasing choices of construction equipment is proposed with two data forms, i.e., 2-dimension uncertain linguistic variables (2DULVs) and real numbers. Firstly, a novel way to derive weights of experts by social network analysis (SNA) is applied considering trust degrees among experts in a social trust network. Secondly, after evaluation index system is established, 2DULVs that include both the linguistic evaluations on alternatives and decision makers’ appraisals on the given evaluation results are applied to represent subjective fuzzy evaluation information, while real numbers are used to represent quantitative values. Thirdly, 2-dimension uncertain linguistic power generalized weighted aggregation (2DULPGWA) operator is applied to aggregate evaluation values among experts. Fourthly, analytic hierarchy process (AHP) and entropy method are utilized to derive combined weights of sub-criteria before the rank can be obtained by the evaluation based on distance from average solution (EDAS) method. Finally, a case study to evaluate multiple choices of loaders is proposed and a comparative analysis is conducted to prove the effectiveness of the proposed framework. This study provides a meaningful guidance for the optimal selection among various types of construction equipment.

An extended prospect theory–VIKOR approach for emergency decision making with 2-dimension uncertain linguistic information

Emergency situations often require high-quality decisions which have to be made within a short period of time. An emergency event is often complex and can cause huge loss of lives and property if a wrong decision is made. Therefore, emergency decision making (EDM) has become a very high-profile research topic in recent years. In this paper, a new integrated approach based on prospect theory and VIKOR (VIsekriterijumska optimizacija i KOm-promisno Resenje), called linguistic PT-VIKOR, is proposed for solving the EDM problems with 2-dimension uncertain linguistic information. First, the preference information and the weights of criteria provided by experts for all statuses are expressed in the form of 2-dimension uncertain linguistic variables (2DULVs). Then, the individual experts’ opinions of each status are aggregated into a group decision matrix according to the aggregation operators of 2DULVs. Next, the group decision matrices of all statuses are transformed into a prospect decision matrix on the basis of the prospect theory, and the VIKOR technique is applied to rank the alternative solutions. Finally, the feasibility and practicability of the proposed linguistic PT-VIKOR approach is illustrated by an illustrate example and a comparative analysis.

Renewable energy project performance evaluation using a hybrid multi-criteria decision-making approach: Case study in Fujian, China

The evaluation of the best renewable energy project (REP) among many alternatives is a complicated multi-criteria decision-making (MCDM) problem, which usually involves several criteria in economy, technicality, environment and society. To solve this problem, a hybrid approach mixing 2-dimension uncertain linguistic variables (2DULVs), a cloud model and an extended TODIM (an acronym in Portuguese of interactive and multicriteria decision making) together to evaluate REPs efficiently is proposed. Firstly, because of the extra reliability assessment, the 2DULVs are adopted by decision-makers (DMs) to evaluate the performance of alternatives. Secondly, given that the cloud model could vividly depict the fuzziness and randomness, a novel conversion model is proposed to transform the 2DULVs into integrated clouds. Thirdly, the extended TODIM approach is used to evaluate and rank REPs considering DMs' psychological behaviors. Following this, the Fujian case study has been provided to demonstrate to verify the feasibility of the hybrid approach. The results show that the most important criterion is the emission reduction of the greenhouse gases (GHG), and the wind power project is selected as the best alternative, but the later sensitivity analysis shows that the optimal alternative is sensitive to the attenuation factor of losses. Finally, a comparative analysis is conducted to demonstrate the correctness and superiority of the proposed approach. The originality of this work is the first time to put forward the model of transforming 2DULVS into integrated cloud.

A 2-dimension uncertain linguistic DEMATEL method for identifying critical success factors in emergency management

Due to the variety and destructiveness of unconventional emergencies, it is of great necessity to analyze and optimize emergency management systematically. The performance of emergency management is often influenced by a lot of factors, and it is not realistic to improve all influential factors simultaneously due to limited resources. To address this concern, a new combined method based on 2-dimension uncertain linguistic variables (2DULVs) and decision-making trial and evaluation laboratory (DEMATEL) is proposed in this paper to determine critical success factors (CSFs) in emergency management. Specifically, the evaluations of influential factors given by decision makers are represented and processed by using 2DULVs. Based on the DEMATEL technique, the cause-effect classification of factors are obtained and the CSFs in emergency management can be found out. Finally, a case study is provided to illustrate the practicality and usefulness of the proposed 2-dimension uncertain linguistic DEMATEL (2DUL-DEMATEL) method. The results show that by enhancing the performance of five CSFs, the effectiveness and efficiency of emergency management could be promoted greatly.

Bonferroni harmonic mean operators based on 2-dimension uncertain linguistic information and their applications in land utilization ratio evaluation

The Bonferroni mean (BM) has the advantages that it can capture the interrelationship among the input arguments, and the Harmonic mean is a conservative average lying between the max and min operators. The 2-dimension uncertain linguistic variables add a subjective evaluation on the reliability of the evaluation results given by decision makers, so they can better express fuzzy information. In this paper, in order to combine the advantages of them, we first propose the 2-dimensional uncertain linguistic weighted Bonferroni mean (2DULWBM) operator. However, it cannot consider the case when the given arguments are too high or too low. So we further proposed the 2-dimensional uncertain linguistic improved weighted Bonferroni harmonic mean (2DULIWBHM) operator, which combine the 2DULWBM with Harmonic Mean. Furthermore, we study some desirable properties and some special cases of them. Further, we develop a new method to deal with some multi-attribute group decision making (MAGDM) problems under 2-dimension uncertain linguistic environment based on the proposed operators. Finally, an illustrative example is given to testify the validity of the developed method by comparing with the other existing methods.

2-Dimension Uncertain Linguistic Generalized Normalized Weighted Geometric Bonferroni Mean and Its Application in Multiple Attribute Decision Making

2-dimension uncertain linguistic variables (2DULVs) are a powerful tool to express the fuzzy or uncertain information, and the weighted Bonferroni mean can not only take the attribute importance into account but also capture the interrelationship between the attributes. However, the traditional Bonferroni mean can only deal with the crisp numbers. In this paper, Bonferroni mean was extended to process the 2DULVs. Firstly, we proposed the normalized weighted geometric Bonferroni mean (NWGBM) operator and the generalized normalized weighted geometric Bonferroni mean (GNWGBM) operator, which have the characteristics of reducibility and also consider the interrelationships between two attributes. Then we introduced the computation rules, characteristics, the expected value and comparison method of the 2DULVs. Further, we developed the 2-dimension uncertain linguistic normalized weighted geometric Bonferroni mean (2DULNWGBM) and the 2-dimension uncertain linguistic generalized normalized weighted geometric Bonferroni mean (2DULGNWGBM), and explored some properties and discussed some special cases of them. Finally, we developed a new decision making method based on these operators, and an example is given to compare with the existing methods.

An Extended VIKOR-Based Approach for Pumped Hydro Energy Storage Plant Site Selection with Heterogeneous Information

The selection of a desirable site for constructing a pumped hydro energy storage plant (PHESP) plays a vital important role in the whole life cycle. However, little research has been done on the site selection of PHESP, which affects the rapid development of PHESP. Therefore, this paper aims to select the most ideal PHESP site from numerous candidate alternatives using the multi-criteria decision-making (MCDM) technique. Firstly, a comprehensive evaluation criteria system is established for the first time. Then, considering quantitative and qualitative criteria coexist in this system, multiple types of representations, including crisp numerical values (CNVs), triangular intuitionistic fuzzy numbers (TIFNs), and 2-dimension uncertain linguistic variables (2DULVs), are employed to deal with heterogeneous criteria information. To determine the weight of criteria and fully take the preference of the decision makers (DMs) into account, the analytic hierarchy process (AHP) method is applied for criteria weighting. After that, an extended Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method is utilized to provide compromise solutions for the PHESP site considering such heterogeneous information. At last, the proposed model is then applied in a case study of Zhejiang province, China to illustrate its practicality and efficiency. The result shows the Changlongshan should be selected as the optimal PHESP.

A Multiple Attribute Group Decision Making Method Based on 2-D Uncertain Linguistic Weighted Heronian Mean Aggregation Operator

2-Dimension uncertain linguistic variables can describe both subjective evaluation result of attributes and reliability of the evaluation results in multiple attribute decision making problems. However, it is difficult to aggregate these evaluation information and give comprehensive results. Heronian mean (HM) has the characteristic of capturing the correlations between aggregated arguments and is extended to solve this problem. The 2-dimension uncertain linguistic weighted HM aggregation( 2DULWHMA) operator is employed in this paper. Firstly, the definition, properties, expectations and the operational laws the 2-dimension uncertain linguistic variables are investigated. Furthermore, the properties of the 2DULWHMA operators, such as commutativity, idempotency and monotonicity, etc. are studied. Some special cases of the generalized parameters in these operators are analyzed. Finally, an example is given to demonstrate the effectiveness and feasibility of the proposed method.

The aggregation operators based on the 2-dimension uncertain linguistic information and their application to decision making

With respect to 2-dimension uncertain linguistic variables, we improve the operational rules of them by transferring the II class uncertain linguistic variables into intuitionistic fuzzy numbers during the process of calculation. It is able to void omitting information and to make the operations more accurate. Firstly, the operational laws of 2-dimension uncertain linguistic information are improved, and their characteristics are proved. Then, 2-dimension uncertain linguistic weighted averaging (2DULWA) operator, 2-dimension uncertain linguistic weighted geometric (2DULWG) operator and 2-dimension uncertain linguistic generalized weighted average (2DULGWA) operator are proposed by new operational laws aforementioned, and some properties and special cases of these operators are discussed. Furthermore, based on the 2DULGWA operator, an approach to the multiple attribute group decision making with 2-dimension uncertain linguistic variables is established. Finally, an illustrative example is given to verify the developed approach and to demonstrate its practicality and effectiveness.

An extended TOPSIS method for multiple attribute decision making problems with unknown weight based on 2-dimension uncertain linguistic variables

An extended TOPSIS method is proposed to solve the multiple attribute decision making problems in which the attribute values take the form of 2-dimension uncertain linguistic variables and the attr...

An extended TOPSIS method for multiple attribute decision making problems with unknown weight based on 2-dimension uncertain linguistic variables

An extended TOPSIS method is proposed to solve the multiple attribute decision making problems in which the attribute values take the form of 2-dimension uncertain linguistic variables and the attribute weight is unknown. Firstly, the operational rules of 2-dimension uncertain linguistic variables are established and the related features are studied, and the distance formula of 2-dimensional uncertain variables is proposed. Then, the attribute weight can be calculated by utilizing the maximum deviation method, and ranking the order of the alternatives is done by TOPSIS method. Finally, an illustrate example is given to show the decision making steps and the effectiveness of this method.

2-Dimension uncertain linguistic power generalized weighted aggregation operator and its application in multiple attribute group decision making

The 2-dimension uncertain linguistic variables add a subjective evaluation on the reliability of the evaluation results given by decision makers, so they can better express fuzzy information. At the same time, the power average (PA) operator has the characteristic of capturing the correlations of the aggregated arguments. In this paper, we propose some power aggregation operators, including 2-dimension uncertain linguistic power generalized aggregation operator (2DULPGA) and 2-dimension uncertain linguistic power generalized weighted aggregation operator (2DULPGWA), and discuss some properties and special cases of them. Finally, with respect to the multiple attribute group decision making problems in which the attribute values take the form of the 2-dimension uncertain linguistic information, the method based on some power generalized aggregation operators is proposed, and two examples are given to verify the developed approach and to demonstrate its effectiveness.

AN APPROACH TO GROUP DECISION MAKING BASED ON 2-DIMENSION UNCERTAIN LINGUISTIC INFORMATION

Based on the definition of 2-dimension linguistic information of multiple attribute decision making problems proposed by Zhu, Zhou and Yang (2009), the information on evaluation is extended to 2-dimension uncertain linguistic variables, and a new method is proposed to solve the multiple-attribute group decision making problems in which the attribute values take the form of 2-dimension uncertain linguistic variables and the attribute weights are unknown. Firstly, the II class of uncertain linguistic information is transformed into the subjective weights of the experts, and then the subjective weights, the similarity degree of experts’ evaluation information and authority weights are aggregated to the comprehensive weights of each expert. By the comprehensive weights, the group decision making matrix is produced by weighting evaluation information of each expert. Then the maximum deviation method is used to calculate the attribute weights and TOPSIS method is proposed to rank the alternatives. Finally, an example is given to illustrate the decision-making steps and the effectiveness of this method.