{"title":"第 2 类模糊环境下的一般新编程问题","authors":"Susanta Banik, Debasish Bhattacharya","doi":"10.1007/s40010-023-00863-7","DOIUrl":null,"url":null,"abstract":"<div><p>The de novo programming technique is used to design an optimal system when the objectives and constraints are linear. It was initially introduced with crisp parameters. Later, de novo programming with fuzzy parameters has been studied to make it more flexible. But the fuzzy set has its limitations too. On the other hand, type-2 fuzzy sets are capable of embracing even those uncertainties that have not been covered or addressed by fuzzy sets. So the general de novo programming problem with interval type-2 fuzzy parameters has been introduced and studied here to make the system more reliable by removing the shortcomings of the human thinking process. This makes de novo programming better for modelling real-life problems than a fuzzy (type-1 fuzzy) logic-based system. The solution procedures for the proposed problem have been illustrated by a solid transportation problem.</p></div>","PeriodicalId":744,"journal":{"name":"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences","volume":"94 1","pages":"99 - 112"},"PeriodicalIF":0.8000,"publicationDate":"2023-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://link.springer.com/content/pdf/10.1007/s40010-023-00863-7.pdf","citationCount":"0","resultStr":"{\"title\":\"General De Novo Programming Problem Under Type-2 Fuzzy Environment\",\"authors\":\"Susanta Banik, Debasish Bhattacharya\",\"doi\":\"10.1007/s40010-023-00863-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The de novo programming technique is used to design an optimal system when the objectives and constraints are linear. It was initially introduced with crisp parameters. Later, de novo programming with fuzzy parameters has been studied to make it more flexible. But the fuzzy set has its limitations too. On the other hand, type-2 fuzzy sets are capable of embracing even those uncertainties that have not been covered or addressed by fuzzy sets. So the general de novo programming problem with interval type-2 fuzzy parameters has been introduced and studied here to make the system more reliable by removing the shortcomings of the human thinking process. This makes de novo programming better for modelling real-life problems than a fuzzy (type-1 fuzzy) logic-based system. The solution procedures for the proposed problem have been illustrated by a solid transportation problem.</p></div>\",\"PeriodicalId\":744,\"journal\":{\"name\":\"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences\",\"volume\":\"94 1\",\"pages\":\"99 - 112\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2023-12-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://link.springer.com/content/pdf/10.1007/s40010-023-00863-7.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s40010-023-00863-7\",\"RegionNum\":4,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the National Academy of Sciences, India Section A: Physical Sciences","FirstCategoryId":"103","ListUrlMain":"https://link.springer.com/article/10.1007/s40010-023-00863-7","RegionNum":4,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
General De Novo Programming Problem Under Type-2 Fuzzy Environment
The de novo programming technique is used to design an optimal system when the objectives and constraints are linear. It was initially introduced with crisp parameters. Later, de novo programming with fuzzy parameters has been studied to make it more flexible. But the fuzzy set has its limitations too. On the other hand, type-2 fuzzy sets are capable of embracing even those uncertainties that have not been covered or addressed by fuzzy sets. So the general de novo programming problem with interval type-2 fuzzy parameters has been introduced and studied here to make the system more reliable by removing the shortcomings of the human thinking process. This makes de novo programming better for modelling real-life problems than a fuzzy (type-1 fuzzy) logic-based system. The solution procedures for the proposed problem have been illustrated by a solid transportation problem.
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