Multi objective programming problem in the hesitant fuzzy environment

Rouhbakhsh, Fatemeh Fayyaz; Ranjbar, Mahdi; Effati, Sohrab; Hassanpour, Hassan

doi:10.1007/s10489-020-01682-8

Cited by 11 publications

(6 citation statements)

References 30 publications

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“…The degree of an element in hesitant fuzzy sets is a subinterval of [0, 1]. Recently, it became one of the common interests for several researchers [ 26 – 30 , 37 , 45 , 46 ] in the various sectors. The interval-valued intuitionistic hesitant fuzzy sets were initially introduced by Zhang [ 44 ] and currently studied by several researchers [ 13 , 20 , 21 , 25 , 33 , 38 ].…”

Section: Literature Reviewmentioning

confidence: 99%

An Interval-Valued Intuitionistic Hesitant Fuzzy Methodology and Application

Bharati

2021

New Gener. Comput.

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Using advantages of interval-valued intuitionistic hesitant fuzzy sets (IVIHFS) for describing the hesitant and intuitionistic decisions of experts and identifying the limitations of previous research works about optimization techniques, this paper introduces a new optimization technique and provides a new computational algorithm, applicable in various real life multiobjective optimization problem (MOOP) of engineering and management sectors, and for this, a new operation between IVIHFSs is first introduced. On the basis of this concept, a stepwise computational algorithm is constructed, and it is an extension of both fuzzy and intuitionistic fuzzy optimization techniques. Finally, the proposed algorithm is illustrated using a production planning problem, and the obtained results are compared with the existing optimization techniques.

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Section: Literature Reviewmentioning

confidence: 99%

An Interval-Valued Intuitionistic Hesitant Fuzzy Methodology and Application

Bharati

2021

New Gener. Comput.

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“… The concept of hesitant fuzzy sets (HFS) [ 20 ], which extends the notion of fuzzy sets, has been proposed to capture situations where multiple membership functions are considered plausible. Various operators have been introduced for aggregating dual hesitant fuzzy sets [ [21] , [22] , [23] ], multi-granulation dual hesitant fuzzy rough sets [ 24 ], and type-2 hesitant fuzzy sets [ 25 , 26 ] that are derived from HFS. Triangular intuitionistic fuzzy sets [ 27 ] and trapezoidal intuitionistic fuzzy sets [ 28 ] are incorporated into linear intuitionistic fuzzy logic, simplifying the aggregation process of fuzzy information.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Dynamic nonlinear simplified neutrosophic sets for multiple-attribute group decision making

Qiu,

Jiang,

Fan

et al. 2024

Heliyon

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“…MCDM theory has made many advances in recent years [ 13 , 14 , 15 ], and has been applied and has achieved good results in location of a fleet [ 16 ], the selection of warships [ 17 ], and information security risk assessment in critical infrastructure [ 18 ]. Hesitant fuzzy sets (HFSs) are one of the MCDM theories, and as an extension of fuzzy sets, they have made achievements in theory as well as in numerous other fields [ 19 , 20 ]. HFSs have been proven as a potential structure to express the uncertainty and vagueness [ 21 , 22 ], which can measure the impact of each attribute on decision making in an integrated way and are more flexible in expressing hesitant information in terms of processing.…”

Section: Introductionmentioning

confidence: 99%

Retrieval and Ranking of Combining Ontology and Content Attributes for Scientific Document

Jiang

Tian

2022

Entropy

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Traditional mathematical search models retrieve scientific documents only by mathematical expressions and their contexts and do not consider the ontological attributes of scientific documents, which result in gaps between the queries and the retrieval results. To solve this problem, a retrieval and ranking model is constructed that synthesizes the information of mathematical expressions with related texts, and the ontology attributes of scientific documents are extracted to further sort the retrieval results. First, the hesitant fuzzy set of mathematical expressions is constructed by using the characteristics of the hesitant fuzzy set to address the multi-attribute problem of mathematical expression matching; then, the similarity of the mathematical expression context sentence is calculated by using the BiLSTM two-way coding feature, and the retrieval result is obtained by synthesizing the similarity between the mathematical expression and the sentence; finally, considering the ontological attributes of scientific documents, the retrieval results are ranked to obtain the final search results. The MAP_10 value of the mathematical expression retrieval results on the Ntcir-Mathir-Wikipedia-Corpus dataset is 0.815, and the average value of the NDCG@10 of the scientific document ranking results is 0.9; these results prove the effectiveness of the scientific document retrieval and ranking method.

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Multi objective programming problem in the hesitant fuzzy environment

Cited by 11 publications

References 30 publications

An Interval-Valued Intuitionistic Hesitant Fuzzy Methodology and Application

An Interval-Valued Intuitionistic Hesitant Fuzzy Methodology and Application

Dynamic nonlinear simplified neutrosophic sets for multiple-attribute group decision making

Retrieval and Ranking of Combining Ontology and Content Attributes for Scientific Document

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