Fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditions
Predicting the exact outcome of a real-life problem, which may occur in various fields like the industrial or healthcare sector, is challenging. Due to high information uncertainty and complicated factors influencing the industrial sector, traditional data-driven prediction approaches can hardly ref...
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| Format: | Article |
| Language: | English |
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Ayandegan Institute of Higher Education,
2024-07-01
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| Series: | Journal of Fuzzy Extension and Applications |
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| Online Access: | https://www.journal-fea.com/article_193524_e64f78eb24316a61a9270723cb42b306.pdf |
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| _version_ | 1832577837245136896 |
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| author | Rajeev Prasad Indrani Maiti Sapan Das Surapati Pramanik Tarni Mandal |
| author_facet | Rajeev Prasad Indrani Maiti Sapan Das Surapati Pramanik Tarni Mandal |
| author_sort | Rajeev Prasad |
| collection | DOAJ |
| description | Predicting the exact outcome of a real-life problem, which may occur in various fields like the industrial or healthcare sector, is challenging. Due to high information uncertainty and complicated factors influencing the industrial sector, traditional data-driven prediction approaches can hardly reflect real changes in practical situations. Fuzzy programming is a powerful prediction reasoning and risk assessment model for uncertain environments. This article mainly explores and applies a modified form of fuzzy programming, namely the Fuzzy Linear Fractional Programming Problem (FLFPP), having the coefficients of the objectives and constraints as Triangular Fuzzy Numbers (TFNs). The FLFPP is converted into an equivalent crisp Multi-Objective Linear Fractional Programming Problem (MOLFPP) and solved individually to associate an aspiration level. Then, by applying the Fuzzy Goal Programming (FGP) technique, the maximum degree of each membership goal is obtained by minimizing the negative deviational variables. We carry out two industrial application simulations in a hypothetical industrial scenario. Our study shows that the proposed model is practical and applicable to the uncertain practical environment to realize the prediction, and the results obtained are compared with those of the existing methods. |
| format | Article |
| id | doaj-art-b8f67fc1b2c74903b4ebb308e5b45324 |
| institution | Kabale University |
| issn | 2783-1442 2717-3453 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Ayandegan Institute of Higher Education, |
| record_format | Article |
| series | Journal of Fuzzy Extension and Applications |
| spelling | doaj-art-b8f67fc1b2c74903b4ebb308e5b453242025-01-30T15:07:12ZengAyandegan Institute of Higher Education,Journal of Fuzzy Extension and Applications2783-14422717-34532024-07-015333035210.22105/jfea.2024.430061.1344193524Fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditionsRajeev Prasad0Indrani Maiti1Sapan Das2Surapati Pramanik3Tarni Mandal4Department of Mathematics, GLA University, Mathura.Department of Mathematics, National Institute of Technology, Jamshedpur, India-831014.Department of Revenue, Ministry of Finance, Govt. of India.Department of Mathematics, Nandalal Ghosh B.T. College, Panpur, P.O.-Naraynpur, North 24 Paraganas, India-743126.Department of Mathematics, National Institute of Technology, Jamshedpur, India-831014.Predicting the exact outcome of a real-life problem, which may occur in various fields like the industrial or healthcare sector, is challenging. Due to high information uncertainty and complicated factors influencing the industrial sector, traditional data-driven prediction approaches can hardly reflect real changes in practical situations. Fuzzy programming is a powerful prediction reasoning and risk assessment model for uncertain environments. This article mainly explores and applies a modified form of fuzzy programming, namely the Fuzzy Linear Fractional Programming Problem (FLFPP), having the coefficients of the objectives and constraints as Triangular Fuzzy Numbers (TFNs). The FLFPP is converted into an equivalent crisp Multi-Objective Linear Fractional Programming Problem (MOLFPP) and solved individually to associate an aspiration level. Then, by applying the Fuzzy Goal Programming (FGP) technique, the maximum degree of each membership goal is obtained by minimizing the negative deviational variables. We carry out two industrial application simulations in a hypothetical industrial scenario. Our study shows that the proposed model is practical and applicable to the uncertain practical environment to realize the prediction, and the results obtained are compared with those of the existing methods.https://www.journal-fea.com/article_193524_e64f78eb24316a61a9270723cb42b306.pdftriangular fuzzy numbermulti-objective linear fractional programmingranking functionfuzzy goal programming |
| spellingShingle | Rajeev Prasad Indrani Maiti Sapan Das Surapati Pramanik Tarni Mandal Fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditions Journal of Fuzzy Extension and Applications triangular fuzzy number multi-objective linear fractional programming ranking function fuzzy goal programming |
| title | Fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditions |
| title_full | Fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditions |
| title_fullStr | Fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditions |
| title_full_unstemmed | Fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditions |
| title_short | Fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditions |
| title_sort | fuzzy goal programming approach for solving linear fractional programming problems with fuzzy conditions |
| topic | triangular fuzzy number multi-objective linear fractional programming ranking function fuzzy goal programming |
| url | https://www.journal-fea.com/article_193524_e64f78eb24316a61a9270723cb42b306.pdf |
| work_keys_str_mv | AT rajeevprasad fuzzygoalprogrammingapproachforsolvinglinearfractionalprogrammingproblemswithfuzzyconditions AT indranimaiti fuzzygoalprogrammingapproachforsolvinglinearfractionalprogrammingproblemswithfuzzyconditions AT sapandas fuzzygoalprogrammingapproachforsolvinglinearfractionalprogrammingproblemswithfuzzyconditions AT surapatipramanik fuzzygoalprogrammingapproachforsolvinglinearfractionalprogrammingproblemswithfuzzyconditions AT tarnimandal fuzzygoalprogrammingapproachforsolvinglinearfractionalprogrammingproblemswithfuzzyconditions |