Multi-attribute decision-making based on the SPIFGIA operators

Wang, Chengqing; Fu, Xiouhua; Meng, Shanshan; He, Yingdong

doi:10.1007/s41066-017-0046-5

Cited by 27 publications

(3 citation statements)

References 56 publications

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“…Briefly, there are two approaches to classify studies in this area: (1) Content Approach; (2) Applied Approach [44]. In the content approach, two main steps are considered for decision-making issues: aggregation of opinions [45][46][47] and method exploitation. In the applied approach, researches on fuzzy numbers with interval values can be classified into five main domains [48]: (1) basic operators in fuzzy space with interval values [49]; (2) group decision [50,51]; (3) combining decision making with linguistic variables [52,53]; (4) matrix of judgment based on priority relations [54] and (5) development of the model of dual interval-valued fuzzy sets [55].…”

Section: Literature Reviewmentioning

confidence: 99%

A Novel Approach for Evaluation of Projects Using an Interval–Valued Fuzzy Additive Ratio Assessment (ARAS) Method: A Case Study of Oil and Gas Well Drilling Projects

et al. 2018

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Abstract:The beginning of the 21st-century resulted in a more developed multi-attribute decisionmaking (MADM) tool and inspired new application areas that have resulted in discoveries in sustainable construction and building life cycle analysis. Construction and civil engineering stand for the central axis of a body consisting of a multidisciplinary (multi-dimensional) world with ties to disciplines constituting the surface, and with the disciplines, as a consequence, tied to each other. When dealing with multi-attribute decision-making problems generally multiple solutions exist, especially when there is a large number of attributes, and the concept of Pareto-optimality is inefficient. The symmetry and structural regularity are essential concepts in many natural and man-made objects and play a crucial role in the design, engineering, and development of the world. The complexity and risks inherent in projects along with different effective indicators for success and failure may contribute to the difficulties in performance evaluation. In such situations, increasing the importance of uncertainty is observed. This paper proposes a novel integrated tool to find a balance between sustainable development, environmental impact and human well-being, i.e., to find symmetry axe with respect to goals, risks, and constraints (attributes) to cope with the complicated problems. The concept of "optimal solution" as the maximum degree of implemented goals (attributes) is very important. The model is built using the most relevant variables cited in the reviewed project literature and integrates two methods: the Step-Wise Weight Assessment Ratio Analysis (SWARA) method and a novel interval-valued fuzzy extension of the Additive Ratio Assessment (ARAS) method. This model was used to solve real case study of oil and gas well drilling projects evaluation. Despite the importance of oil and gas well drilling projects, there is lack of literature that describes and evaluates performance in this field projects. On the other hand, no structured assessment methodology has been presented for these types of projects. Given the limited research on performance evaluation in oil & gas well-drilling projects, the research identifies a set of performance criteria and proposes an evaluation model using fuzzy Delphi method. An illustrative example shows that the proposed method is a useful and alternative decision-making method.

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Section: Literature Reviewmentioning

confidence: 99%

A Novel Approach for Evaluation of Projects Using an Interval–Valued Fuzzy Additive Ratio Assessment (ARAS) Method: A Case Study of Oil and Gas Well Drilling Projects

et al. 2018

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“…The INS is a subclass of the NS and generalization of the IFS and IVIFS, which was proposed by Wang [6]. Motivated by some aggregation operators and decision-making methods for IFSs, IVIFSs, and NSs [14][15][16][17][18][19], a lot of theories about INSs have been put forward successively, and their basic concepts and aggregation tools play important roles in practical applications. For instance, Wang et al [6] defined the basic operational relations for INSs and Zhang et al [20] pointed out some drawbacks of these operational laws and improved them.…”

Section: Introductionmentioning

confidence: 99%

Generalized Interval Neutrosophic Choquet Aggregation Operators and Their Applications

Zhang

Park

2018

Symmetry

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The interval neutrosophic set (INS) is a subclass of the neutrosophic set (NS) and a generalization of the interval-valued intuitionistic fuzzy set (IVIFS), which can be used in real engineering and scientific applications. This paper aims at developing new generalized Choquet aggregation operators for INSs, including the generalized interval neutrosophic Choquet ordered averaging (G-INCOA) operator and generalized interval neutrosophic Choquet ordered geometric (G-INCOG) operator. The main advantages of the proposed operators can be described as follows: (i) during decision-making or analyzing process, the positive interaction, negative interaction or non-interaction among attributes can be considered by the G-INCOA and G-INCOG operators; (ii) each generalized Choquet aggregation operator presents a unique comprehensive framework for INSs, which comprises a bunch of existing interval neutrosophic aggregation operators; (iii) new multi-attribute decision making (MADM) approaches for INSs are established based on these operators, and decision makers may determine the value of λ by different MADM problems or their preferences, which makes the decision-making process more flexible; (iv) a new clustering algorithm for INSs are introduced based on the G-INCOA and G-INCOG operators, which proves that they have the potential to be applied to many new fields in the future.

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“…Because of the inherent complexity and uncertainty of the decision situation or the existence of multiple and conflicting objectives, decision-making problems are complex and difficult; particularly in the era of big data, decision making becomes more complicated because the huge amounts of decision information and alternatives are continuously growing. Many new decision-making methods, such as granular computing techniques [1,[6][7][8][9][10], have been proposed for expressing complex or uncertain information in decision-making processes and solving decision-making problems [11][12][13][14][15][16][17][18][19][20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

A New Hesitant Fuzzy Linguistic TOPSIS Method for Group Multi-Criteria Linguistic Decision Making

2017

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Hesitant fuzzy linguistic decision making is a focus point in linguistic decision making, in which the main method is based on preference ordering. This paper develops a new hesitant fuzzy linguistic TOPSIS method for group multi-criteria linguistic decision making; the method is inspired by the TOPSIS method and the preference degree between two hesitant fuzzy linguistic term sets (HFLTSs). To this end, we first use the preference degree to define a pseudo-distance between two HFLTSs and analyze its properties. Then we present the positive (optimistic) and negative (pessimistic) information of each criterion provided by each decision maker and aggregate these by using weights of decision makers to obtain the hesitant fuzzy linguistic positive and negative ideal solutions. On the basis of the proposed pseudo-distance, we finally obtain the positive (negative) ideal separation matrix and a new relative closeness degree to rank alternatives. We also design an algorithm based on the provided method to carry out hesitant fuzzy linguistic decision making. An illustrative example shows the elaboration of the proposed method and comparison with the symbolic aggregation-based method, the hesitant fuzzy linguistic TOPSIS method and the hesitant fuzzy linguistic VIKOR method; it seems that the proposed method is a useful and alternative decision-making method.

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Multi-attribute decision-making based on the SPIFGIA operators

Cited by 27 publications

References 56 publications

A Novel Approach for Evaluation of Projects Using an Interval–Valued Fuzzy Additive Ratio Assessment (ARAS) Method: A Case Study of Oil and Gas Well Drilling Projects

A Novel Approach for Evaluation of Projects Using an Interval–Valued Fuzzy Additive Ratio Assessment (ARAS) Method: A Case Study of Oil and Gas Well Drilling Projects

Generalized Interval Neutrosophic Choquet Aggregation Operators and Their Applications

A New Hesitant Fuzzy Linguistic TOPSIS Method for Group Multi-Criteria Linguistic Decision Making

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