A multihesitant fuzzy linguistic multicriteria decision-making approach for logistics outsourcing with incomplete weight information

2017 ◽  
Vol 25 (3) ◽  
pp. 831-856 ◽  
Author(s):  
Jing Wang ◽  
Jian-qiang Wang ◽  
Zhang-peng Tian ◽  
Dong-yan Zhao
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Logistics Outsourcing ◽  
Multicriteria Decision ◽  
Incomplete Weight ◽  
Incomplete Weight Information ◽  
Fuzzy Linguistic

scholarly journals Spherical Cubic Fuzzy Extended TOPSIS Method and Its Application in Multicriteria Decision-Making

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Tehreem ◽  
Amjad Hussain ◽  
Ahmed Alsanad ◽  
Mogeeb A. A. Mosleh
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Maximum Deviation ◽  
Topsis Method ◽  
Multicriteria Decision ◽  
Numerical Example ◽  
Structured Analysis ◽  
Incomplete Weight ◽  
Incomplete Weight Information

This paper aims to propose a new methodology for spherical cubic fuzzy (SCF) multicriteria decision-making (MCDM) utilizing the TOPSIS method that uses incomplete weight information. At first, the maximum deviation model is suggested to determine the criteria of weight values. An MCDM methodology is introduced using SCF information, based on the proposed method. Also, to validate the effectiveness of the proposed information, a numerical example is given. Finally, a comprehensive and structured analysis of existing work in comparison with previous work is given.

scholarly journals The Evaluation of Mineral Resources Development Efficiency Based on Hesitant Fuzzy Linguistic Approach and Modified TODIM

2018 ◽  
Vol 2018 ◽  
pp. 1-9 ◽  
Author(s):  
Pu Li ◽  
Xudong Chen ◽  
Xinyi Qu ◽  
Qi Xu
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Mineral Resources ◽  
Evaluation Process ◽  
Multicriteria Decision ◽  
Actual Evaluation ◽  
Panxi Area ◽  
Linguistic Approach ◽  
Fuzzy Linguistic ◽  
Resources Development

The evaluation of mineral resources development efficiency is a typical multicriteria decision-making issue. Meanwhile, due to the limited existing technology, there might be subjectivity, ambiguity, and inaccuracy of the measurement of the evaluation index of mineral resources development efficiency. In this paper, we, considering the incomplete information, use the hesitant fuzzy linguistic approach to describe the psychological hesitation and ambiguity of the decision-maker in the actual evaluation process and then construct the general model of the development efficiency evaluation of the mineral resources by using the hesitant fuzzy linguistic terms sets and modified TODIM. Finally, this paper takes the Panxi area as an example to study the development efficiency of vanadium-titanium magnetite. The results show that the hesitant fuzzy linguistic multicriteria decision-making (MCDM) approach can be implemented to mineral resources evaluation and resources management.

scholarly journals Hesitant Fuzzy Linguistic Multicriteria Decision-Making Method Based on Generalized Prioritized Aggregation Operator

2014 ◽  
Vol 2014 ◽  
pp. 1-16 ◽  
Author(s):  
Jia-ting Wu ◽  
Jian-qiang Wang ◽  
Jing Wang ◽  
Hong-yu Zhang ◽  
Xiao-hong Chen
Keyword(s):  
Decision Making ◽  
Multicriteria Decision Making ◽  
Comparison Method ◽  
Aggregation Operator ◽  
New Approach ◽  
Multicriteria Decision ◽  
Scale Functions ◽  
Prioritized Aggregation Operator ◽  
Prioritized Aggregation Operators ◽  
Fuzzy Linguistic

Based on linguistic term sets and hesitant fuzzy sets, the concept of hesitant fuzzy linguistic sets was introduced. The focus of this paper is the multicriteria decision-making (MCDM) problems in which the criteria are in different priority levels and the criteria values take the form of hesitant fuzzy linguistic numbers (HFLNs). A new approach to solving these problems is proposed, which is based on the generalized prioritized aggregation operator of HFLNs. Firstly, the new operations and comparison method for HFLNs are provided and some linguistic scale functions are applied. Subsequently, two prioritized aggregation operators and a generalized prioritized aggregation operator of HFLNs are developed and applied to MCDM problems. Finally, an illustrative example is given to illustrate the effectiveness and feasibility of the proposed method, which are then compared to the existing approach.

scholarly journals Extension of Axiomatic Design Method for Fuzzy Linguistic Multiple Criteria Group Decision Making with Incomplete Weight Information

2012 ◽  
Vol 2012 ◽  
pp. 1-17 ◽  
Author(s):  
Ming Li
Keyword(s):  
Decision Making ◽  
Information Content ◽  
Group Decision Making ◽  
Group Decision ◽  
Axiomatic Design ◽  
Weight Vector ◽  
Multiple Criteria ◽  
Incomplete Weight ◽  
Incomplete Weight Information ◽  
Fuzzy Linguistic

Axiomatic design (AD) provides a framework to describe design objects and a set of axioms to evaluate relations between intended functions and means by which they are achieved. It has been extended to evaluate alternatives in engineering under fuzzy environment. With respect to multiple criteria group decision making (MCDM) with incomplete weight information under fuzzy linguistic environment, a new method is proposed. In the method, the fuzzy axiomatic design based on triangle representation model is used to aggregate the linguistic evaluating information. In order to get the weight vector of the criteria, we establish a nonlinear optimization model based on the basic ideal of fuzzy axiomatic design (FAD), by which the criteria weights can be determined. It is based on the concept that the optimal alternative should have the least weighted information content. Then, the weighted information content is derived by summing weighted information content for each criterion. The alternative that has the least total weighted information content is the best. Finally, a numerical example is used to illustrate the availability of the proposed method.

scholarly journals Pain Treatment Evaluation in COVID-19 Patients with Hesitant Fuzzy Linguistic Multicriteria Decision-Making

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
G. Didem Batur Sir ◽  
Ender Sir
Keyword(s):  
Decision Making ◽  
Pain Treatment ◽  
Multicriteria Decision Making ◽  
Accurate Method ◽  
Solution Procedure ◽  
Analytic Hierarchy ◽  
Multicriteria Decision ◽  
Appropriate Treatment ◽  
Choice Of Treatment ◽  
Fuzzy Linguistic

The coronavirus disease 2019 (COVID-19) has emerged as a worldwide pandemic since March 2020. Although most patients complain of moderate or severe pain, these symptoms are generally underestimated and appropriate treatment is not applied. This study aims to guide physicians in selecting and ranking various alternatives for the treatment of pain in COVID-19 patients. However, the choice of treatment for pain requires the consideration of many different conflicting criteria. Therefore, we have studied this problem as a multicriteria decision-making problem. Throughout the solution procedure, first, the criteria and subcriteria affecting the preferences are defined. Then, weight values are determined with respect to these criteria, as they have different degrees of importance for the problem. At this stage, hesitant fuzzy linguistic term sets (HFLTSs) are used, and thus, experts can convey their ideas more accurately. In this first phase of the study, an HFLTS integrated Analytic Hierarchy Process (AHP) method is utilized. Subsequently, possible treatment alternatives are evaluated by using the Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method. According to the results obtained by considering expert evaluations, the most preferred treatment is the administration of paracetamol, followed by interventional treatments, opioids, and nonsteroidal anti-inflammatory drugs (NSAIDs), respectively. With this study, it is ensured that a more accurate method is followed by eliminating possible mistakes due to the subjective evaluations of experts in the process of determining pain treatment. This method can also be used in different patient and disease groups.

Sign in / Sign up

Export Citation Format

Share Document