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<Article>
<Journal>
<PublisherName>OICC Press</PublisherName>
<JournalTitle>Fuzzy Optimization and Modeling Journal (FOMJ)</JournalTitle>
<Issn>2676-7007</Issn>
<Volume>4</Volume>
<Issue>4</Issue>
<PubDate PubStatus="epublish">
<Year>2024</Year>
<Month>02</Month>
<Day>10</Day>
</PubDate>
</Journal>
<ArticleTitle>A Reliable Approach in Solving Multi-Attribute Decision-Making Problems through Fuzzy Rule-Base System and Z-numbers</ArticleTitle>
<VernacularTitle></VernacularTitle>
<FirstPage>82</FirstPage>
<LastPage>105</LastPage>
<ELocationID EIdType="doi">10.30495/fomj.2023.1998695.1124</ELocationID>
<Language>EN</Language>
<AuthorList>
<Author>
<FirstName>Saeed</FirstName>
<LastName>Bahrami</LastName>
<Affiliation>Department of Educational Science, Farhangian University, Tehran, Iran</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Mahmonir</FirstName>
<LastName>Bayanati</LastName>
<Affiliation>Faculty of Technology and Industrial Management, Health and Industry Research Centre, West Tehran Branch, Islamic Azad University, Tehran, Iran</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Mohammad Reza</FirstName>
<LastName>Nasiri Janagha</LastName>
<Affiliation>Department of Industrial Engineering, Lahijan Branch, Islamic Azad University, Lahijan, Iran</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Saman</FirstName>
<LastName>Malekian</LastName>
<Affiliation>Department of Industrial Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Milad</FirstName>
<LastName>Abolghasemian</LastName>
<Affiliation>Department of Industrial Engineering, Lahijan Branch, Islamic Azad University, Lahijan, Iran</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
<Author>
<FirstName>Adel</FirstName>
<LastName>Pourghader Chobar</LastName>
<Affiliation>Department of Industrial Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran</Affiliation>
<Identifier Source="ORCID"></Identifier>
</Author>
</AuthorList>
<PublicationType>Journal Article</PublicationType>
<History>
<PubDate PubStatus="received">
<Year>2024</Year>
<Month>02</Month>
<Day>10</Day>
</PubDate>
</History>
<Abstract>Multi-Attribute Decision Making (MADM) process is the most well-known branch of decision making and it is one of the most important tasks that have received a lot of attention in many areas. In solving MADM issues, the parameters of decision-making are often faced with problems, such as imprecise, vague, uncertain, or incomplete information which lead to inaccurate decision-making. To cope with these problems, the researchers apply fuzzy set theory as the best-developed approach. Among different fuzzy methods, the fuzzy rule-based system (FRBS) due to its flexibility, simplicity, and experts&amp;#039; knowledge modeling is an adequate technique for solving MADM problems. The main objective of this study is to apply experts&amp;#039; opinions by Z-numbers in MADM issues to enhance the accuracy of the decision-making process. The fundamental issue in solving MADM problems is that inadequate information in the experts&amp;#039; opinions leads to some degree of uncertainty in decisions. Indeed, in FRBS research to ranking, the reliability level (Z-numbers) in experts&amp;#039; opinions within the decision-making process has not been taken into account. Whereas, the Z-numbers play a key role in the decision-making process to reach more precise decisions affecting the final ranking results. In the proposed approach (Z-FRBS), by considering experts&amp;#039; opinions in the form of Z-numbers to deal with inadequate information and modeling experts&amp;#039; knowledge through FRBS, the process of making a decision is performed without using conventional techniques which resulted in a more accurate solving MADM problems. The effectiveness and validity of the proposed method was approved with an illustrative example, sensitivity analysis, and comparison with three other validated method.</Abstract>
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<Object Type="keyword">
<Param Name="value">Group decision-making</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Linguistic Variables</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Multi-attribute decision-making</Param>
</Object>
<Object Type="keyword">
<Param Name="value">Z-number</Param>
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<Object Type="keyword">
<Param Name="value">fuzzy rule-based</Param>
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