{"title":"np完全","authors":"Ganesh Gopalakrishnan","doi":"10.1201/9781315148175-19","DOIUrl":null,"url":null,"abstract":"Why study problems in NP? Papadimitriou and Steiglitz, page 351: “The recognition versions of all reasonable combinatorial optimization problems are in NP , . . . (because) . . . combinatorial optimization problems aim for the optimal design of objects. It is reasonable to expect that, once found, the optimal solution can be written down concisely, and thus serve as a certificate for the recognition version.”","PeriodicalId":139478,"journal":{"name":"Automata and Computability","volume":"30 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"NP-Completeness\",\"authors\":\"Ganesh Gopalakrishnan\",\"doi\":\"10.1201/9781315148175-19\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Why study problems in NP? Papadimitriou and Steiglitz, page 351: “The recognition versions of all reasonable combinatorial optimization problems are in NP , . . . (because) . . . combinatorial optimization problems aim for the optimal design of objects. It is reasonable to expect that, once found, the optimal solution can be written down concisely, and thus serve as a certificate for the recognition version.”\",\"PeriodicalId\":139478,\"journal\":{\"name\":\"Automata and Computability\",\"volume\":\"30 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Automata and Computability\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1201/9781315148175-19\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Automata and Computability","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1201/9781315148175-19","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Why study problems in NP? Papadimitriou and Steiglitz, page 351: “The recognition versions of all reasonable combinatorial optimization problems are in NP , . . . (because) . . . combinatorial optimization problems aim for the optimal design of objects. It is reasonable to expect that, once found, the optimal solution can be written down concisely, and thus serve as a certificate for the recognition version.”