<?xml version="1.0" encoding="UTF-8"?> <!DOCTYPE ArticleSet PUBLIC "-//NLM//DTD PubMed 2.7//EN" "https://dtd.nlm.nih.gov/ncbi/pubmed/in/PubMed.dtd"> <ArticleSet> <Article> <Journal> <PublisherName>Kharazmi University</PublisherName> <JournalTitle>International Journal of Supply and Operations Management</JournalTitle> <Issn>23831359</Issn> <Volume>11</Volume> <Issue>1</Issue> <PubDate PubStatus="epublish"> <Year>2024</Year> <Month>02</Month> <Day>01</Day> </PubDate> </Journal> <ArticleTitle>Two Novel Generalized Information Measures for Fuzzy Sets</ArticleTitle> <VernacularTitle></VernacularTitle> <FirstPage>43</FirstPage> <LastPage>53</LastPage> <ELocationID EIdType="pii">2921</ELocationID> <ELocationID EIdType="doi">10.22034/ijsom.2023.109243.2271</ELocationID> <Language>EN</Language> <AuthorList> <Author> <FirstName>Ashok</FirstName> <LastName>Kumar</LastName> <Affiliation>Applied Sciences, Faculty, Chitkara University, Himachal Pradesh, India</Affiliation> <Identifier Source="ORCID">000000024299626X</Identifier> </Author> <Author> <FirstName>Krishan</FirstName> <LastName>Kumar</LastName> <Affiliation>Deen Bandhu Chhotu Ram University of Science and Technology, Haryana-131039, India</Affiliation> </Author> <Author> <FirstName>Madhu</FirstName> <LastName>Gupta</LastName> <Affiliation>Chitkara University School of Engineering and Technology, Chitkara University, Himachal Pradesh, India</Affiliation> <Identifier Source="ORCID">0000000150622199</Identifier> </Author> <Author> <FirstName>Komal Kumari</FirstName> <LastName>Deswal</LastName> <Affiliation>Atal Shiksha Kunj, Atal Nagar, Barotiwala, Solan, Himachal Pradesh</Affiliation> </Author> <Author> <FirstName>Bhagwan</FirstName> <LastName>Das</LastName> <Affiliation>Government College Haryana-126102, India</Affiliation> </Author> </AuthorList> <PublicationType>Journal Article</PublicationType> <History> <PubDate PubStatus="received"> <Year>2021</Year> <Month>07</Month> <Day>16</Day> </PubDate> </History> <Abstract>In the present manuscript, it is our utmost aim and objective to comprehensively and extensively expound upon two highly innovative and remarkably novel information measures that have been adeptly and appropriately extended to encompass fuzzy sets. These measures have undergone a rigorous and meticulous scrutiny and examination with regard to axiomatic principles, and have evinced numerous and manifold advantageous properties, thus providing a compelling and highly persuasive validation of their reliability, credibility, and overall effectiveness. It is of paramount importance to note that the measures in question have been meticulously and painstakingly designed with the express aim and purpose of effectively quantifying the extent of information that is inextricably embedded and enmeshed within fuzzy sets, and are firmly grounded in the foundational and bedrock principles of information theory, which is an indisputably and irrefutably significant and substantial academic discipline. Our contributions to the field of study are truly and incontestably unparalleled, and offer a fresh, innovative, and unprecedented perspective on the study of fuzzy sets and their associated information content, which is of immense and inestimable value to the overall advancement and progress of the academic discipline.</Abstract> <ObjectList> <Object Type="keyword"> <Param Name="value">Fuzzy Set</Param> </Object> <Object Type="keyword"> <Param Name="value">Fuzzy Entropy</Param> </Object> <Object Type="keyword"> <Param Name="value">Membership Function</Param> </Object> <Object Type="keyword"> <Param Name="value">measure</Param> </Object> <Object Type="keyword"> <Param Name="value">Vagueness</Param> </Object> </ObjectList> <ArchiveCopySource DocType="pdf">http://www.ijsom.com/article_2921_c58a6e2e2c775e2a27247f16a9b1fd1c.pdf</ArchiveCopySource> </Article> </ArticleSet>