{"title":"动态规划","authors":"N. Hastings","doi":"10.1201/9781315275987-6","DOIUrl":null,"url":null,"abstract":"2 Algorithmic Paradigms Greed. Build up a solution incrementally, myopically optimizing some local criterion. Divide-and-conquer. Break up a problem into two sub-problems, solve each sub-problem independently, and combine solution to sub-problems to form solution to original problem. Dynamic programming. Break up a problem into a series of overlapping sub-problems, and build up solutions to larger and larger sub-problems. 3 Dynamic Programming History Bellman. Pioneered the systematic study of dynamic programming in the 1950s. Etymology. Dynamic programming = planning over time.","PeriodicalId":380681,"journal":{"name":"Engineering Optimization Theory and Practice","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2849","resultStr":"{\"title\":\"Dynamic Programming\",\"authors\":\"N. Hastings\",\"doi\":\"10.1201/9781315275987-6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"2 Algorithmic Paradigms Greed. Build up a solution incrementally, myopically optimizing some local criterion. Divide-and-conquer. Break up a problem into two sub-problems, solve each sub-problem independently, and combine solution to sub-problems to form solution to original problem. Dynamic programming. Break up a problem into a series of overlapping sub-problems, and build up solutions to larger and larger sub-problems. 3 Dynamic Programming History Bellman. Pioneered the systematic study of dynamic programming in the 1950s. Etymology. Dynamic programming = planning over time.\",\"PeriodicalId\":380681,\"journal\":{\"name\":\"Engineering Optimization Theory and Practice\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2849\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Optimization Theory and Practice\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1201/9781315275987-6\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Optimization Theory and Practice","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1201/9781315275987-6","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
2 Algorithmic Paradigms Greed. Build up a solution incrementally, myopically optimizing some local criterion. Divide-and-conquer. Break up a problem into two sub-problems, solve each sub-problem independently, and combine solution to sub-problems to form solution to original problem. Dynamic programming. Break up a problem into a series of overlapping sub-problems, and build up solutions to larger and larger sub-problems. 3 Dynamic Programming History Bellman. Pioneered the systematic study of dynamic programming in the 1950s. Etymology. Dynamic programming = planning over time.