The Experts below are selected from a list of 5511 Experts worldwide ranked by ideXlab platform
Zeshui Xu - One of the best experts on this subject based on the ideXlab platform.
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computation of generalized Linguistic Term sets based on fuzzy logical algebras for multi attribute decision making
Granular Computing, 2020Co-Authors: Zhen Ming, Zeshui XuAbstract:Computational models of various Linguistic Term sets whose evaluation scales are the identity functions have been extensively investigated. Among these models, although the virtual Linguistic model is the most straightforward and convenient for the calculations, the operations are not closed on the given scales. In this paper, we develop the fuzzy logical algebras-based virtual Linguistic model. We propose the generalized Linguistic Term sets based on general strictly increasing functions with the existing Linguistic Term sets as special cases, and define some novel operational laws and measures such as similarity measures, distance measures and entropy measures for them. Then we provide some Linguistic aggregation operators for the generalized Linguistic Term sets in multi-attribute decision making. Particularly, when these operators are reduced to the existing ones, it is shown that the proposed operational laws can be considered as a modification of the existing ones in related literature. Based on the proposed operators, a multi-attribute decision-making model is built, and a method for deTermining the objective–subjective weight vector in generalized Linguistic Term sets are put forward. Finally, an illustrative example is presented for verifying our models and methods and a comparative analysis with the existing methods is made.
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distance measures for hesitant intuitionistic fuzzy Linguistic Term sets based on a risk factor parameter
International Journal of Computers and Applications, 2019Co-Authors: Shahzad Faizi, Zeshui Xu, Tabasam Rashid, Sohail ZafarAbstract:ABSTRACTWe propose notions of some distance measures between two hesitant intuitionistic fuzzy Linguistic Term sets (HIFLTSs). Weighted distance measures between two collections of HIFLTSs are also...
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todim based multi criteria decision making method with hesitant fuzzy Linguistic Term sets
Artificial Intelligence Review, 2019Co-Authors: Huibing Wang, Zeshui XuAbstract:As a popular tool for modeling the qualitative assessment information, the hesitant fuzzy Linguistic Term sets (HFLTSs) can allow the decision makes or experts to give several possible Linguistic Terms to rate the objects with respect to the criterion. Although there exist many multi-criteria decision-making methods put forward for handling the HFLTSs, they were developed based on the assumption that the decision makers can always provide completely rational assessments and they do not take the decision makers’ psychological behaviors into consideration. In this paper, the traditional TODIM (an acronym in Portuguese for interactive multi-criteria decision making) method is extended to handle the HFLTSs based on the novel comparison function and distance measure. Firstly, we put forward a novel function for comparing two HFLTSs more effectively. After that, a novel hesitance degree function as well as some novel distance measures are given for HFLTSs. Then we apply them to extend the traditional TODIM method for solving the HFLTSs. Finally, a practical example concerning the evaluation and ranking of several satellite launching centers is provided to illustrate the validity and applicability of the proposed method.
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a projection method for multiple attribute group decision making with probabilistic Linguistic Term sets
International Journal of Machine Learning and Cybernetics, 2019Co-Authors: Xiaofang Zhang, Zeshui Xu, Huchang LiaoAbstract:In multiple attribute group decision making (MAGDM) processes, decision makers often use hesitant fuzzy Linguistic Term sets (HFLTSs) to express their opinions. However, it is incapable of representing the importance degrees or weights of different Linguistic Terms. The probabilistic Linguistic Term set (PLTS) gives each Linguistic Term a probability to denote their importance degree, and thus is more suitable for group decision making problems where the distribution information is available. In this paper, the PLTSs are utilized to express the experts’ assessments on each alternative with respect to each attribute in the MAGDM problem. Additionally, we establish two optimization models to derive the attribute weights. Then we propose a projection model to calculate the alternatives’ projections on both the positive and negative ideal solutions. A practical decision making problem about crossover development is given to validate the effectiveness of the projection method with PLTS information. Finally, we make some comparisons between the projection method and other existing methods, meanwhile, the advantages and limitations of the projection model are summarized.
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inclusion measures of probabilistic Linguistic Term sets and their application in classifying cities in the economic zone of chengdu plain
Applied Soft Computing, 2019Co-Authors: Ming Tang, Huchang Liao, Yilu Long, Zeshui XuAbstract:Abstract The probabilistic Linguistic Term set is a powerful tool to express and characterize people’s cognitive complex information and thus has obtained a great development in the last several years. To better use the probabilistic Linguistic Term sets in decision making, information measures such as the distance measure, similarity measure, entropy measure and correlation measure should be defined. However, as an important kind of information measure, the inclusion measure has not been defined by scholars. This study aims to propose the inclusion measure for probabilistic Linguistic Term sets. Formulas to calculate the inclusion degrees are put forward Then, we introduce the normalized axiomatic definitions of the distance, similarity and entropy measures of probabilistic Linguistic Term sets to construct a unified framework of information measures for probabilistic Linguistic Term sets. Based on these definitions, we present the relationships and transformation functions among the distance, similarity, entropy and inclusion measures. We believe that more formulas to calculate the distance, similarity, inclusion degree and entropy can be induced based on these transformation functions. Finally, we put forward an orthogonal clustering algorithm based on the inclusion measure and use it in classifying cities in the Economic Zone of Chengdu Plain, China.
Huchang Liao - One of the best experts on this subject based on the ideXlab platform.
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unbalanced double hierarchy Linguistic Term set the topsis method for multi expert qualitative decision making involving green mine selection
Information Fusion, 2019Co-Authors: Ziguo Fu, Huchang LiaoAbstract:Abstract The double hierarchy Linguistic Term set is a Linguistic technique to elaborately and accurately represent complex Linguistic information for qualitative decision-making problems. Considering that unbalanced semantics may appear in the first and second hierarchy Linguistic Term sets, the unbalanced double hierarchy Linguistic Term set (UDHLTS) is proposed in this paper. To characterize the unbalanced distribution of semantics of the second hierarchy Linguistic Terms, we propose three Linguistic scale functions with cognitive bias parameters. Then, a non-linear fitting method is presented to deTermine these parameters. Combining the first and second hierarchy Linguistic Term set, we construct eight semantic models with distinct risk appetite parameters and Linguistic cognitive bias parameters to capture the semantics of Linguistic Terms in the UDHLTS. In this way, we can use specific semantic model to represent experts’ opinions associated with the UDHLTS. In addition, by using the semantic model of the UDHLTS, Linguistic information from different experts can be compared and aggregated quantitatively. To illustrate the applicability of the UDHLTS, we develop a UDHL-TOPSIS method for multi-expert qualitative decision making problems. An engineering example concerning green mine selection is given to illustrate the proposed method.
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a projection method for multiple attribute group decision making with probabilistic Linguistic Term sets
International Journal of Machine Learning and Cybernetics, 2019Co-Authors: Xiaofang Zhang, Zeshui Xu, Huchang LiaoAbstract:In multiple attribute group decision making (MAGDM) processes, decision makers often use hesitant fuzzy Linguistic Term sets (HFLTSs) to express their opinions. However, it is incapable of representing the importance degrees or weights of different Linguistic Terms. The probabilistic Linguistic Term set (PLTS) gives each Linguistic Term a probability to denote their importance degree, and thus is more suitable for group decision making problems where the distribution information is available. In this paper, the PLTSs are utilized to express the experts’ assessments on each alternative with respect to each attribute in the MAGDM problem. Additionally, we establish two optimization models to derive the attribute weights. Then we propose a projection model to calculate the alternatives’ projections on both the positive and negative ideal solutions. A practical decision making problem about crossover development is given to validate the effectiveness of the projection method with PLTS information. Finally, we make some comparisons between the projection method and other existing methods, meanwhile, the advantages and limitations of the projection model are summarized.
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inclusion measures of probabilistic Linguistic Term sets and their application in classifying cities in the economic zone of chengdu plain
Applied Soft Computing, 2019Co-Authors: Ming Tang, Huchang Liao, Yilu Long, Zeshui XuAbstract:Abstract The probabilistic Linguistic Term set is a powerful tool to express and characterize people’s cognitive complex information and thus has obtained a great development in the last several years. To better use the probabilistic Linguistic Term sets in decision making, information measures such as the distance measure, similarity measure, entropy measure and correlation measure should be defined. However, as an important kind of information measure, the inclusion measure has not been defined by scholars. This study aims to propose the inclusion measure for probabilistic Linguistic Term sets. Formulas to calculate the inclusion degrees are put forward Then, we introduce the normalized axiomatic definitions of the distance, similarity and entropy measures of probabilistic Linguistic Term sets to construct a unified framework of information measures for probabilistic Linguistic Term sets. Based on these definitions, we present the relationships and transformation functions among the distance, similarity, entropy and inclusion measures. We believe that more formulas to calculate the distance, similarity, inclusion degree and entropy can be induced based on these transformation functions. Finally, we put forward an orthogonal clustering algorithm based on the inclusion measure and use it in classifying cities in the Economic Zone of Chengdu Plain, China.
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water security evaluation based on the todim method with probabilistic Linguistic Term sets
Soft Computing, 2019Co-Authors: Yixin Zhang, Zeshui Xu, Huchang LiaoAbstract:Nowadays, water security is becoming increasingly prominent and the water security problem becomes a primary bottleneck restricting China’s future sustainable development. Water security in China is thus worth conducting an in-depth study. This paper aims to explore an effective water security evaluation method. Based on the proposed definition of water security, an evaluation index system of water security is first built from the perspective of “pressure–state–response” conceptual model. Considering the indicators’ uncertainty and the decision makers’ (DMs’) limited knowledge, the DMs usually use Linguistic Terms to express their judgements. As a new type of Linguistic variable, probabilistic Linguistic Term set (PLTS) not only allows the DMs to express their judgements with multiple Linguistic Terms but also can reflect the DMs’ different preference degrees over these possible Linguistic Terms. For the water security issue under probabilistic Linguistic environment, a programming model is developed to derive the attribute weights. Then, the TODIM (an acronym in Portuguese for interactive multi-criteria decision making) method, which considers the psychological factors of the DMs, is used to evaluate water security based on the PLTS. Furthermore, a case study is conducted and some discussions and comparative analysis are carried out according to the case results.
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About the Double Hierarchy Linguistic Term Set and Its Extensions
2019Co-Authors: Huchang LiaoAbstract:Practical decision-making process mainly consists of three aspects: collecting assessment information, processing assessment information, and obtaining the final decision-making result. In this process, the first and most important step is to represent the original meaning of the assessment information of decision-makers (DMs). Considering that the natural languages are more in line with the real thought of DMs than the crisp values, so the research of how to represent qualitative information becomes increasingly popular and attracted many experts. Then, The fuzzy Linguistic approach was proposed to deal with the natural language and the concept of computing with words was further defined. Motivated by the fuzzy Linguistic approach, the double hierarchy Linguistic Term set (DHLTS) and its extensions were defined to represent the complex Linguistic information, and lots of researches have been done about the DHLTS and its extensions. In this paper, we mainly review the existing research about the DHLTS and its extensions from different angles including decision-making methodologies, preference relations and information measures. Then, we make a short comment about them and discuss some research directions for the future.
Francisco Herrera - One of the best experts on this subject based on the ideXlab platform.
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double hierarchy hesitant fuzzy Linguistic Term set and multimoora method
Information Fusion, 2017Co-Authors: Huchang Liao, Zeshui Xu, Francisco HerreraAbstract:We define the double hierarchy Linguistic Term set (DHLTS).We propose the double hierarchy hesitant fuzzy Linguistic Term set (DHHFLTS).We establish some operational laws and properties of the DHHFLTS.We develop a MULTIMOORA method on the basis of DHHFLTS.We apply this MULTIMOORA method to deal with a practical decision making problem. In recent years, hesitant fuzzy Linguistic Term sets (HFLTSs) have been studied by many scholars and are becoming gradually mature. However, some shortcomings of HFLTS also emerged. To describe the complex Linguistic Terms or Linguistic Term sets more accurately and reasonably, in this paper, we introduce the novel concepts named double hierarchy Linguistic Term set (DHLTS) and double hierarchy hesitant fuzzy Linguistic Term set (DHHFLTS). The operational laws and properties of the DHHFLTSs are developed as well.Afterwards, we investigate the multiple criteria decision making model with double hierarchy hesitant fuzzy Linguistic information. We develop a double hierarchy hesitant fuzzy Linguistic MULTIMOORA (DHHFL-MULTIMOORA) method to solve it. Furthermore, we apply the DHHFL-MULTIMOORA method to deal with a practical case about selecting the optimal city in China by evaluating the implementation status of haze controlling measures. Some comparisons between the DHHFL-MULTIMOORA method and the hesitant fuzzy Linguistic TOPSIS method are provided to show the advantages of the proposed method.
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Connecting the numerical scale model to the unbalanced Linguistic Term sets
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2014Co-Authors: Yucheng Dong, Cong-cong Li, Francisco HerreraAbstract:Herrera and Martinez initiated a 2-tuple fuzzy Linguistic representation model for computing with words (CWW). In addition to the Herrera and Martinez model, two different models based on Linguistic 2-tuples (i.e., the model of Herrera et al. and the numerical scale model) have been developed to deal with Term sets that are not uniformly and symmetrically distributed, i.e., unbalanced Linguistic Term sets (ULTSs). Both the model of Herrera et al. and the numerical scale model can deal with ULTSs, so a challenge is naturally proposed to analysts: how to compare these two different models. In this study, we provide a connection between the model of Herrera et al. and the numerical scale model. The results show that the model of Herrera et al. provides a new approach to set a numerical scale. Furthermore, we prove the equivalence of the Linguistic computational models between the model of Herrera et al. and the numerical scale model, if the numerical scale is set based on the model of Herrera et al.
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FUZZ-IEEE - Connecting the numerical scale model to the unbalanced Linguistic Term sets
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2014Co-Authors: Yucheng Dong, Cong-cong Li, Francisco HerreraAbstract:Herrera and Martinez initiated a 2-tuple fuzzy Linguistic representation model for computing with words (CWW). In addition to the Herrera and Martinez model, two different models based on Linguistic 2-tuples (i.e., the model of Herrera et al. and the numerical scale model) have been developed to deal with Term sets that are not uniformly and symmetrically distributed, i.e., unbalanced Linguistic Term sets (ULTSs). Both the model of Herrera et al. and the numerical scale model can deal with ULTSs, so a challenge is naturally proposed to analysts: how to compare these two different models. In this study, we provide a connection between the model of Herrera et al. and the numerical scale model. The results show that the model of Herrera et al. provides a new approach to set a numerical scale. Furthermore, we prove the equivalence of the Linguistic computational models between the model of Herrera et al. and the numerical scale model, if the numerical scale is set based on the model of Herrera et al.
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hesitant fuzzy Linguistic Term sets for decision making
IEEE Transactions on Fuzzy Systems, 2012Co-Authors: Rosa M Rodriguez, Luis Martinez, Francisco HerreraAbstract:Dealing with uncertainty is always a challenging problem, and different tools have been proposed to deal with it. Recently, a new model that is based on hesitant fuzzy sets has been presented to manage situations in which experts hesitate between several values to assess an indicator, alternative, variable, etc. Hesitant fuzzy sets suit the modeling of quantitative settings; however, similar situations may occur in qualitative settings so that experts think of several possible Linguistic values or richer expressions than a single Term for an indicator, alternative, variable, etc. In this paper, the concept of a hesitant fuzzy Linguistic Term set is introduced to provide a Linguistic and computational basis to increase the richness of Linguistic elicitation based on the fuzzy Linguistic approach and the use of context-free grammars by using comparative Terms. Then, a multicriteria Linguistic decision-making model is presented in which experts provide their assessments by eliciting Linguistic expressions. This decision model manages such Linguistic expressions by means of its representation using hesitant fuzzy Linguistic Term sets.
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hesitant fuzzy Linguistic Term sets
2011Co-Authors: Rosa M Rodriguez, Luis Martinez, Francisco HerreraAbstract:Dealing with vague or imprecise information has been always a challenging problem. Different tools have been proposed to manage that uncertainty. A new model based on hesitant fuzzy sets was presented to manage situations where experts hesitate among several values to assess alternatives, variables, etc. Hesitant fuzzy sets models quantitative settings, however, it could occur similar situations but in qualitative settings, where experts think of several possible Linguistic values or richer expressions than a single Linguistic Term to assess alternatives, variables, etc. In this contribution the aim is to introduce the concept of Hesitant Fuzzy Linguistic Term Sets (HFLTS) that will provide a Linguistic elicitation based on the fuzzy Linguistic approach and the use of context-free grammars.
Luis Martinez - One of the best experts on this subject based on the ideXlab platform.
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Type-2 Fuzzy Envelope of Hesitant Fuzzy Linguistic Term Set: A New Representation Model of Comparative Linguistic Expression
IEEE Transactions on Fuzzy Systems, 2019Co-Authors: Rosa M Rodriguez, Hani Hagras, Luis MartinezAbstract:The use of hesitant fuzzy Linguistic Term sets (HFLTS) contributes to the elicitation of comparative Linguistic expressions (CLEs) in decision contexts when experts hesitate among different Linguistic Terms to provide their assessments. Since the existing representation models for Linguistic expressions based on HFLTS do not properly consider the uncertainty caused by the inherent vagueness of such Linguistic expressions, it is necessary to improve their modeling to cope with such vagueness. In this paper, we propose a new fuzzy envelope for the HFLTS in form of type-2 fuzzy sets for representing CLEs. Such an envelope overcomes the limitation of existing representations in coping with inherent uncertainties and facilitates the processes of computing with words for Linguistic decision making problems dealing with CLEs.
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Uncertainty Measures of Extended Hesitant Fuzzy Linguistic Term Sets
IEEE Transactions on Fuzzy Systems, 2018Co-Authors: Rosa M Rodriguez, Luis MartinezAbstract:A hesitant fuzzy Linguistic Term set (HFLTS) is defined as a subset of ordered consecutive Linguistic Terms, and it has been successfully applied to deal with experts hesitation in decision-making problems when experts have to provide their assessments. This concept has been recently extended to manage ordered consecutive and nonconsecutive Linguistic Terms, called extended HFLTS (EHFLTS), which is used in Linguistic group decision-making problems to represent the group opinion without loss of information. This paper is focused on studying how to measure the uncertainty presented by the information of an EHFLTS and also of an HFLTS. To do so, a new comprehensive entropy measure for EHFLTSs, which considers two types of uncertainty, fuzziness and hesitation, is proposed. The construction methods of the two types of entropy are studied and a comprehensive entropy formula is defined. Finally, a comparative study is carried out to analyze the results obtained from the proposed entropy measures.
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On the use of Hesitant Fuzzy Linguistic Term Set in FLINTSTONES
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2014Co-Authors: Francisco J. Estrella, Rosa M Rodriguez, Macarena Espiniila, Luis MartinezAbstract:The use of Linguistic information to model and manage uncertainty in Decision Making (DM) has been a key subject of many proposals in the literature. The 2-tuple Linguistic model and its extensions in Linguistic DM has been very successful and extensive due to their flexibility and accuracy. Flintstones is a novel fuzzy Linguistic decision tool enhancement suite that implements tools to facilitate the solving of Linguistic DM problems that model the Linguistic information with such a model and its extensions. However, both the 2-tuple Linguistic model and Flintstones can not deal with uncertain situations modelled Linguistically in which experts hesitate among several Linguistic Terms. For these cases, recently, it has been proposed the use of Hesitant Fuzzy Linguistic Term Sets (HFLTS) that have attracted a lot of research interest, mainly regarding its application in DM. Hence in this contribution it is proposed an extended version of Flintstones that includes the ability and functionality of dealing with HFLTS in Linguistic decision problems and enables the integration, validity and performance of hesitant Linguistic decision models and operators.
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FUZZ-IEEE - On the use of Hesitant Fuzzy Linguistic Term Set in FLINTSTONES
2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 2014Co-Authors: Francisco J. Estrella, Rosa M Rodriguez, Macarena Espiniila, Luis MartinezAbstract:The use of Linguistic information to model and manage uncertainty in Decision Making (DM) has been a key subject of many proposals in the literature. The 2-tuple Linguistic model and its extensions in Linguistic DM has been very successful and extensive due to their flexibility and accuracy. Flintstones is a novel fuzzy Linguistic decision tool enhancement suite that implements tools to facilitate the solving of Linguistic DM problems that model the Linguistic information with such a model and its extensions. However, both the 2-tuple Linguistic model and Flintstones can not deal with uncertain situations modelled Linguistically in which experts hesitate among several Linguistic Terms. For these cases, recently, it has been proposed the use of Hesitant Fuzzy Linguistic Term Sets (HFLTS) that have attracted a lot of research interest, mainly regarding its application in DM. Hence in this contribution it is proposed an extended version of Flintstones that includes the ability and functionality of dealing with HFLTS in Linguistic decision problems and enables the integration, validity and performance of hesitant Linguistic decision models and operators.
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a fuzzy representation for the semantics of hesitant fuzzy Linguistic Term sets
2014Co-Authors: Rosa M Rodriguez, Luis MartinezAbstract:Recently, a concept of hesitant fuzzy Linguistic Term sets (HFLTS) to facilitate elicitation of Linguistic information when experts hesitate among several Linguistic Terms to express their preferences in Linguistic decision problems was presented. To carry out computations with such type of information, it was introduced the concept of envelope of an HFLTS. This envelope is represented by a symbolic Linguistic interval, hence the results do not keep the fuzzy representation. Therefore, this contribution proposes a new fuzzy envelope to represent HFLTS by means of a fuzzy membership function that keeps the fuzzy representation in computational processes with HFLTS.
Shyiming Chen - One of the best experts on this subject based on the ideXlab platform.
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fuzzy decision making based on likelihood based comparison relations of hesitant fuzzy Linguistic Term sets and hesitant fuzzy Linguistic operators
Information Sciences, 2015Co-Authors: Shyiming ChenAbstract:In this paper, we propose a new fuzzy decision making method and propose a new fuzzy group decision making method based on the proposed likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets and the proposed hesitant fuzzy Linguistic weighted average (HFLWA) operator, the proposed hesitant fuzzy Linguistic weighted geometric (HFLWG) operator, the proposed hesitant fuzzy Linguistic ordered weighted average (HFLOWA) operator, and the proposed hesitant fuzzy Linguistic ordered weighted geometric (HFLOWG) operator of hesitant fuzzy Linguistic Term sets. The proposed fuzzy decision making method can overcome the drawback of Rodriguez et al.'s method (2012) and Wei et al.'s method (2014) for fuzzy decision making, which cannot distinguish the preference order of alternatives in some situations. The proposed fuzzy group decision making method is more flexible than Rodriguez et al.'s method (2013) for fuzzy group decision making because it considers different hesitant fuzzy Linguistic operators for fuzzy group decision making. The proposed methods provide us with a useful way for decision making in fuzzy environments.
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multicriteria Linguistic decision making based on hesitant fuzzy Linguistic Term sets and the aggregation of fuzzy sets
Information Sciences, 2014Co-Authors: Shyiming Chen, Jia-an HongAbstract:In this paper, we present a new method for multicriteria Linguistic decision making based on hesitant fuzzy Linguistic Term sets using the pessimistic attitude and the optimistic attitude of the decision-maker. The proposed method aggregates the fuzzy sets in each hesitant fuzzy Linguistic Term set into a fuzzy set and performs the @a-cut operations to these aggregated fuzzy sets to get intervals, respectively, where @[email protected]?(0,1]. For each alternative, it performs the minimum operations and the maximum operations among the obtained intervals to get the derived intervals, respectively, where the minimum operation and the maximum operation among intervals denote the pessimistic attitude and the optimistic attitude of the decision-maker, respectively. Then, for each alternative, it uses the likelihood method for ranking the priority between the obtained intervals to get the preference order of the alternatives for the decision-maker with the pessimistic attitude and the optimistic attitude, respectively. The proposed method is more flexible than the existing methods for multicriteria Linguistic decision making due to the fact that it considers the pessimistic attitude and the optimistic attitude of the decision-maker.
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A new fuzzy multiple criteria decision making method based on likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets and a-cuts of fuzzy sets
2014 International Conference on Machine Learning and Cybernetics, 2014Co-Authors: Shyiming ChenAbstract:In this paper, we propose the concept of likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets to compare two hesitant fuzzy Linguistic Term sets based on a-cuts of fuzzy sets. We also propose a new fuzzy multiple criteria decision making method based on likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets and the a -cuts of fuzzy sets. The proposed fuzzy multiple criteria decision making method has the following advantages: 1) it can overcome the drawback of the existing methods which cannot distinguish the preference order of alternatives in some situations and 2) it allows experts to use a fuzzy target to reflect his/her attitude for increasing the flexibility.
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ICMLC - A new fuzzy multiple criteria decision making method based on likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets and a-cuts of fuzzy sets
2014 International Conference on Machine Learning and Cybernetics, 2014Co-Authors: Shyiming ChenAbstract:In this paper, we propose the concept of likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets to compare two hesitant fuzzy Linguistic Term sets based on a-cuts of fuzzy sets. We also propose a new fuzzy multiple criteria decision making method based on likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets and the a -cuts of fuzzy sets. The proposed fuzzy multiple criteria decision making method has the following advantages: 1) it can overcome the drawback of the existing methods which cannot distinguish the preference order of alternatives in some situations and 2) it allows experts to use a fuzzy target to reflect his/her attitude for increasing the flexibility.
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A new group decision making method based on likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets
2014 IEEE International Conference on Systems Man and Cybernetics (SMC), 2014Co-Authors: Shyiming ChenAbstract:In this paper, we present a new group decision making method based on likelihood-based comparison relations of hesitant fuzzy Linguistic Term sets. The likelihood-based comparison relation of hesitant fuzzy Linguistic Term sets is used to compare two hesitant fuzzy Linguistic Term sets. The fuzzy optimistic target, the fuzzy neutral target and the fuzzy pessimistic target are used to reflect experts' attitudes. The proposed method is more flexible than the existing method due to the fact that it considers experts' attitudes for group decision making. It provides us with a useful way for group decision making in a fuzzy environment.
