Neutrosophic linear programming using possibilistic mean
The paper discusses the concept of fuzzy set theory, interval-valued fuzzy set, intuitionistic fuzzy set, interval-valued intuitionistic fuzzy set, neutrosophic set and its operational laws. The paper presents the α , β , γ - cut of single-valued triangular neutrosophic numbers and introduces the ar...
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| Veröffentlicht in: | Soft computing (Berlin, Germany) Germany), 2020-11, Vol.24 (22), p.16847-16867 |
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| container_title | Soft computing (Berlin, Germany) |
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| creator | Khatter, Kiran |
| description | The paper discusses the concept of fuzzy set theory, interval-valued fuzzy set, intuitionistic fuzzy set, interval-valued intuitionistic fuzzy set, neutrosophic set and its operational laws. The paper presents the
α
,
β
,
γ
-
cut of single-valued triangular neutrosophic numbers and introduces the arithmetic operations of triangular neutrosophic numbers using
α
,
β
,
γ
-
cut. Then, possibilistic mean of truth membership function, indeterminacy membership function and falsity membership function is defined. The proposed approach converts each triangular neutrosophic number in linear programming problem to weighted value using possibilistic mean to determine the crisp linear programming problem. The proposed approach also considers the risk attitude of expert while deciding the parameters of linear programming model. |
| doi_str_mv | 10.1007/s00500-020-04980-y |
| format | Article |
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α
,
β
,
γ
-
cut of single-valued triangular neutrosophic numbers and introduces the arithmetic operations of triangular neutrosophic numbers using
α
,
β
,
γ
-
cut. Then, possibilistic mean of truth membership function, indeterminacy membership function and falsity membership function is defined. The proposed approach converts each triangular neutrosophic number in linear programming problem to weighted value using possibilistic mean to determine the crisp linear programming problem. The proposed approach also considers the risk attitude of expert while deciding the parameters of linear programming model.</description><identifier>ISSN: 1432-7643</identifier><identifier>EISSN: 1433-7479</identifier><identifier>DOI: 10.1007/s00500-020-04980-y</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Artificial Intelligence ; Computational Intelligence ; Control ; Decision making ; Engineering ; Fuzzy set theory ; Fuzzy sets ; Linear programming ; Mathematical Logic and Foundations ; Mathematical programming ; Mechatronics ; Methodologies and Application ; Numbers ; Optimization techniques ; Programming languages ; Researchers ; Robotics ; Set theory</subject><ispartof>Soft computing (Berlin, Germany), 2020-11, Vol.24 (22), p.16847-16867</ispartof><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2020</rights><rights>Springer-Verlag GmbH Germany, part of Springer Nature 2020.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c319t-2e493540a85f06c479a4cebd809a3a593ca6cfcd7634d02b2f98d0067c0dc4193</citedby><cites>FETCH-LOGICAL-c319t-2e493540a85f06c479a4cebd809a3a593ca6cfcd7634d02b2f98d0067c0dc4193</cites><orcidid>0000-0002-1000-6102</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00500-020-04980-y$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2918058896?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>314,780,784,21388,27924,27925,33744,41488,42557,43805,51319,64385,64389,72469</link.rule.ids></links><search><creatorcontrib>Khatter, Kiran</creatorcontrib><title>Neutrosophic linear programming using possibilistic mean</title><title>Soft computing (Berlin, Germany)</title><addtitle>Soft Comput</addtitle><description>The paper discusses the concept of fuzzy set theory, interval-valued fuzzy set, intuitionistic fuzzy set, interval-valued intuitionistic fuzzy set, neutrosophic set and its operational laws. The paper presents the
α
,
β
,
γ
-
cut of single-valued triangular neutrosophic numbers and introduces the arithmetic operations of triangular neutrosophic numbers using
α
,
β
,
γ
-
cut. Then, possibilistic mean of truth membership function, indeterminacy membership function and falsity membership function is defined. The proposed approach converts each triangular neutrosophic number in linear programming problem to weighted value using possibilistic mean to determine the crisp linear programming problem. The proposed approach also considers the risk attitude of expert while deciding the parameters of linear programming model.</description><subject>Artificial Intelligence</subject><subject>Computational Intelligence</subject><subject>Control</subject><subject>Decision making</subject><subject>Engineering</subject><subject>Fuzzy set theory</subject><subject>Fuzzy sets</subject><subject>Linear programming</subject><subject>Mathematical Logic and Foundations</subject><subject>Mathematical programming</subject><subject>Mechatronics</subject><subject>Methodologies and Application</subject><subject>Numbers</subject><subject>Optimization techniques</subject><subject>Programming languages</subject><subject>Researchers</subject><subject>Robotics</subject><subject>Set 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making</topic><topic>Engineering</topic><topic>Fuzzy set theory</topic><topic>Fuzzy sets</topic><topic>Linear programming</topic><topic>Mathematical Logic and Foundations</topic><topic>Mathematical programming</topic><topic>Mechatronics</topic><topic>Methodologies and Application</topic><topic>Numbers</topic><topic>Optimization techniques</topic><topic>Programming languages</topic><topic>Researchers</topic><topic>Robotics</topic><topic>Set theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Khatter, Kiran</creatorcontrib><collection>CrossRef</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One 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The paper presents the
α
,
β
,
γ
-
cut of single-valued triangular neutrosophic numbers and introduces the arithmetic operations of triangular neutrosophic numbers using
α
,
β
,
γ
-
cut. Then, possibilistic mean of truth membership function, indeterminacy membership function and falsity membership function is defined. The proposed approach converts each triangular neutrosophic number in linear programming problem to weighted value using possibilistic mean to determine the crisp linear programming problem. The proposed approach also considers the risk attitude of expert while deciding the parameters of linear programming model.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s00500-020-04980-y</doi><tpages>21</tpages><orcidid>https://orcid.org/0000-0002-1000-6102</orcidid></addata></record> |
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| ispartof | Soft computing (Berlin, Germany), 2020-11, Vol.24 (22), p.16847-16867 |
| issn | 1432-7643 1433-7479 |
| language | eng |
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| source | ProQuest Central UK/Ireland; SpringerLink Journals - AutoHoldings; ProQuest Central |
| subjects | Artificial Intelligence Computational Intelligence Control Decision making Engineering Fuzzy set theory Fuzzy sets Linear programming Mathematical Logic and Foundations Mathematical programming Mechatronics Methodologies and Application Numbers Optimization techniques Programming languages Researchers Robotics Set theory |
| title | Neutrosophic linear programming using possibilistic mean |
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