{"title":"dp求解器:自动动态规划","authors":"Z. Kátai, Attila Elekes","doi":"10.2478/ausi-2021-0017","DOIUrl":null,"url":null,"abstract":"Abstract Dynamic programming (DP) is a widely used optimization method with several applications in various fields of science. The DP problem solving process can be divided in two phases: mathematical part and programming part. There are a number of researchers for whom the mathematical part is available, but they are not familiar with computer programming. In this paper we present a software tool that automates the programming part of DP and allows users to solve problems based only on their mathematical approach. The application builds up the “d-graph model” of the problem to be solved and applies the “d-variant” of the corresponding single source shortest path algorithm. In addition, we report experimental results regarding the e ciency of the tool relative to the Matlab implementation.","PeriodicalId":41480,"journal":{"name":"Acta Universitatis Sapientiae Informatica","volume":"10 1","pages":"361 - 372"},"PeriodicalIF":0.3000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DP-solver: automating dynamic programming\",\"authors\":\"Z. Kátai, Attila Elekes\",\"doi\":\"10.2478/ausi-2021-0017\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Dynamic programming (DP) is a widely used optimization method with several applications in various fields of science. The DP problem solving process can be divided in two phases: mathematical part and programming part. There are a number of researchers for whom the mathematical part is available, but they are not familiar with computer programming. In this paper we present a software tool that automates the programming part of DP and allows users to solve problems based only on their mathematical approach. The application builds up the “d-graph model” of the problem to be solved and applies the “d-variant” of the corresponding single source shortest path algorithm. In addition, we report experimental results regarding the e ciency of the tool relative to the Matlab implementation.\",\"PeriodicalId\":41480,\"journal\":{\"name\":\"Acta Universitatis Sapientiae Informatica\",\"volume\":\"10 1\",\"pages\":\"361 - 372\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Acta Universitatis Sapientiae Informatica\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/ausi-2021-0017\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, THEORY & METHODS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Acta Universitatis Sapientiae Informatica","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/ausi-2021-0017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
Abstract Dynamic programming (DP) is a widely used optimization method with several applications in various fields of science. The DP problem solving process can be divided in two phases: mathematical part and programming part. There are a number of researchers for whom the mathematical part is available, but they are not familiar with computer programming. In this paper we present a software tool that automates the programming part of DP and allows users to solve problems based only on their mathematical approach. The application builds up the “d-graph model” of the problem to be solved and applies the “d-variant” of the corresponding single source shortest path algorithm. In addition, we report experimental results regarding the e ciency of the tool relative to the Matlab implementation.