A systematic review on multi-criteria group decision-making methods based on weights: analysis and classification scheme

Interest in group decision-making (GDM) has been increasing prominently over the last decade. Access to global databases, sophisticated sensors which can obtain multiple inputs or complex problems requiring opinions from several experts have driven interest in data aggregation. Consequently, the field has been widely studied from several viewpoints and multiple approaches have been proposed. Nevertheless, there is a lack of general framework. Moreover, this problem is exacerbated in the case of experts’ weighting methods, one of the most widely-used techniques to deal with multiple source aggregation. This lack of general classification scheme, or a guide to assist expert knowledge, leads to ambiguity or misreading for readers, who may be overwhelmed by the large amount of unclassified information currently available. To invert this situation, a general GDM framework is presented which divides and classifies all data aggregation techniques, focusing on and expanding the classification of experts’ weighting methods in terms of analysis type by carrying out an in-depth literature review. Results are not only classified but analysed and discussed regarding multiple characteristics, such as MCDMs in which they are applied, type of data used, ideal solutions considered or when they are applied. Furthermore, general requirements supplement this analysis such as initial influence, or component division considerations. As a result, this paper provides not only a general classification scheme and a detailed analysis of experts’ weighting methods but also a road map for researchers working on GDM topics or a guide for experts who use these methods. Furthermore, six significant contributions for future research pathways are provided in the conclusions.The first author acknowledges support from the Spanish Ministry of Universities [grant number FPU18/01471]. The second and third author wish to recognize their support from the Serra Hunter program. Finally, this work was supported by the Catalan agency AGAUR through its research group support program (2017SGR00227). This research is part of the R&D project IAQ4EDU, reference no. PID2020-117366RB-I00, funded by MCIN/AEI/10.13039/ 501100011033.Peer ReviewedPostprint (published version

A decision-making framework based on the Fermatean hesitant fuzzy distance measure and TOPSIS

A particularly useful assessment tool for evaluating uncertainty and dealing with fuzziness is the Fermatean fuzzy set (FFS), which expands the membership and non-membership degree requirements. Distance measurement has been extensively employed in several fields as an essential approach that may successfully disclose the differences between fuzzy sets. In this article, we discuss various novel distance measures in Fermatean hesitant fuzzy environments as research on distance measures for FFS is in its early stages. These new distance measures include weighted distance measures and ordered weighted distance measures. This justification serves as the foundation for the construction of the generalized Fermatean hesitation fuzzy hybrid weighted distance (DGFHFHWD) scale, as well as the discussion of its weight determination mechanism, associated attributes and special forms. Subsequently, we present a new decision-making approach based on DGFHFHWD and TOPSIS, where the weights are processed by exponential entropy and normal distribution weighting, for the multi-attribute decision-making (MADM) issue with unknown attribute weights. Finally, a numerical example of choosing a logistics transfer station and a comparative study with other approaches based on current operators and FFS distance measurements are used to demonstrate the viability and logic of the suggested method. The findings illustrate the ability of the suggested MADM technique to completely present the decision data, enhance the accuracy of decision outcomes and prevent information loss

Priority Modeling for Public Urban Park Development in Feasible Locations using GIS, Intuitionistic Fuzzy AHP, and Fuzzy TOPSIS

As feasible locations of public urban park in Bogor Municipality have been acquired in a previous study, decision makers are urgently needed to be informed on which locations should be prioritized for public urban park (PUP) development. Therefore, this study aggregates four multi-spatial criteria for PUP development priority modeling, namely distance to slum neighborhood, accessibility, slope, and land value. These four criteria in form of vector datasets were weighted using intuitionistic fuzzy analytical hierarchy process (IF-AHP) to consider the hesitancy, vagueness, and fuzziness might arise from experts’ judgement as well as from multi-spatial data processing. Resulted criteria weights from IF-AHP show that accessibility weight 0.261, land value weight 0.259, distance to slum weight 0.255, and slope weight 0.225, respectively. Criteria weights were inputted into fuzzy technique for order preference by similarity to the ideal solution (TOPSIS) and geographic information system (GIS) to rank location priority. Results from fuzzy TOPSIS show that very high priority class which has the biggest CCi values range (0.654-0.76) provides 0.14 km2 area of feasible PUP development scattered in 10 locations. The biggest area for feasible PUP development is generated by medium priority class (CCi values 0.439-0.546) in 26 locations and approximately area of 0.38 km2

Research on VIKOR group decision making using WOWA operator based on interval Pythagorean triangular fuzzy numbers

A new decision-making method based on interval Pythagorean triangular fuzzy numbers is proposed for fuzzy information decision-making problems, taking the advantages of interval Pythagorean fuzzy numbers and triangular fuzzy numbers into account. The VIse Kriterijumski Optimizacioni Racun (VIKOR) group decision-making method is based on the Weighted Ordered Weighted Average (WOWA) operator of interval Pythagorean triangular fuzzy numbers (IVPTFWOWA). First, this article provides the definition of the IVPTFWOWA operator and proves its degeneracy, idempotence, monotonicity, and boundedness. Second, the decision steps of the VIKOR decision method using the IVPTFWOWA operator are presented. Finally, the scientificity and effectiveness of the proposed method were verified through case studies and comparative discussions. The research results indicate that the following: (1) the IVPTFWOWA operator combines interval Pythagorean fuzzy numbers and triangular fuzzy numbers, complementing the shortcomings of the two fuzzy numbers, and can characterize fuzzy information on continuous geometry, thereby reducing decision errors caused by inaccurate and fuzzy information; (2) the VIKOR decision-making method based on the IVPTFWOWA operator applies comprehensive weights, fully considering the positional weights of the scheme attributes and the weights of raters, and fully utilizing the attribute features of decision-makers and cases; and (3) compared to other methods, there is a significant gap between the decision results obtained using this method, making it easier to identify the optimal solution

Weighting methods for multi-criteria decision making technique

Determining criteria weights is a problem that arises frequently in many multi-criteria decision-making (MCDM) techniques. Taking into account the fact that the weights of criteria can significantly influence the outcome of the decision-making process, it is important to pay particular attention to the objectivity factors of criteria weights. This paper provides an overview of different weighting methods applicable to multi-criteria optimization techniques. There are a lot of concept been reported from the literature that are very useful in solving multicriteria problems. The present work emphasized on the use of these weighting methods in determining the criteria preference of each criterion to bring about desirable properties and in order to establish and satisfy a multiple measure of performance across all the criteria selected by identifying the best options possible. And from the results, it shows that subjective weighting methods are easy and straight forward in terms of their computations than the objective weighting methods which derived their information from each criterion by adopting a mathematical function to determine the weights without the decision-maker’s input,. This can be seen from the pairwise comparison which gives an internal storage and random access memory of a smart phone a weight value of 0.33 and 0.22 respectively as they have the highest criteria weights.Keywords: Multi-criteria, Decision-making, Relative importance, Alternative, Criteri

Fuzzy Techniques for Decision Making 2018

Zadeh's fuzzy set theory incorporates the impreciseness of data and evaluations, by imputting the degrees by which each object belongs to a set. Its success fostered theories that codify the subjectivity, uncertainty, imprecision, or roughness of the evaluations. Their rationale is to produce new flexible methodologies in order to model a variety of concrete decision problems more realistically. This Special Issue garners contributions addressing novel tools, techniques and methodologies for decision making (inclusive of both individual and group, single- or multi-criteria decision making) in the context of these theories. It contains 38 research articles that contribute to a variety of setups that combine fuzziness, hesitancy, roughness, covering sets, and linguistic approaches. Their ranges vary from fundamental or technical to applied approaches

Underground Mining Method Selection With the Hesitant Fuzzy Linguistic Gained and Lost Dominance Score Method

Underground mining method selection is a critical decision problem for available underground ore deposits in exploitation design. As many comprehensive factors, such as physical parameters, economic benefits, and environmental effects, are claimed to be established and a group of experts are involved in the issue, the underground mining method selection is deemed as a multiple experts multiple criteria decision making problem. Classical mining method assessment exists some gaps due to the way of representing opinions. To address this matter, a hesitant fuzzy linguistic gained and lost dominance score method is investigated in this paper. To enhance the flexibility and gain more information, mining planning engineers are allowed to convey their knowledge using hesitant fuzzy linguistic term sets in the underground mining method selection process. A novel score function of hesitant fuzzy linguistic term set is introduced to compare any hesitant fuzzy linguistic term sets. Then, based on the score function, a weight determining function is proposed to calculate the weights of criteria, which can magnify the ‘‘importance’’ and ‘‘unimportance’’ of criteria. To select the mining method, the hesitant fuzzy linguistic gained and dominance score method is developed. A case study concerning selecting a extraction method for a real mine in Yunnan province of China is presented to illustrate the applicability of the proposed method. The effectiveness of the proposed method is finally verified by comparing with other ranking methodsNational Natural Science Foundation of China under Grant 71501135 and Grant 717711562019 Sichuan Planning Project of Social Science under Grant SC18A0072018 Key Project of the Key Research Institute of Humanities and Social Sciences in Sichuan Province under Grant Xq18A01 and Grant LYC18-02Electronic Commerce and Modern Logistics Research Center Program, Key Research Base of Humanities and Social Science, Sichuan Provincial Education Department, under Grant DSWL18-2Spark Project of Innovation, Sichuan University, under Grant 2018hhs-43Scientific Research Foundation for Excellent Young Scholars, Sichuan University, under Grant 2016SCU04A23

Integrated Frameworks for Effective Multi-criteria Decision Making in Reliability Centred Maintenance of Industrial Machines

No abstract availabl

A hierarchical integration method under social constraints to maximize satisfaction in multiple criteria group decision making systems

Aggregating multiple opinions or assessments in a decision has always been a challenging field topic for researchers. Over the last decade, different approaches, mainly based on weighting data sources or decision-makers (DMs), have been proposed to resolve this issue, although social choice theory, focused on frameworks to combine individual opinions, is generally overlooked. To resolve this situation, a novel methodology is developed in this paper based on social choice theory and statistical mathematics. This method innovates by dividing the assessment into components which provides a multiple assessment analysis, assigning weights to each source regarding their position compared to the group for each considered criteria. This multiple-weighting process maximises individual and group satisfaction. Furthermore, the method makes it possible to manage previously assigned influence. An example is given to illustrate the proposed methodology. Additionally, sensitivity analysis is performed and comparisons with other methods are made. Finally, conclusions are presented.The first author acknowledges support from the Spanish Ministry of Education, Culture and Sports [grant number FPU18/01471]. The second and third author wish to recognise their support from the Serra Hunter programme. Finally, this work was supported by the Catalan agency AGAUR through its research group support program (2017SGR00227). This research is part of the R&D project IAQ4EDU, reference no. PID2020-117366RB-I00, funded by MCIN/AEI/10.13039/501100011033.Peer ReviewedPostprint (published version