{"title":"混合整数线性规划自动化测试装配R包的比较","authors":"Michael R. Peabody","doi":"10.1080/15366367.2022.2151081","DOIUrl":null,"url":null,"abstract":"ABSTRACT Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical representation of the test assembly problem that looks for the statistically optimal solution. Because MIP is a mathematical representation, changes to the test assembly problem typically involve only minor changes to the programming. This review focuses on comparing two free and open-source R packages for mixed integer linear programming: inlinelpSolveAPI and inlineompr. Programming style (with code provided), ease of use, run time, and other considerations will be examined. Solvers from other open-source platforms (e.g. Python, Julia) will also be discussed. Code and sample data are also provided.","PeriodicalId":46596,"journal":{"name":"Measurement-Interdisciplinary Research and Perspectives","volume":null,"pages":null},"PeriodicalIF":0.6000,"publicationDate":"2023-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Comparison of R Packages for Automated Test Assembly with Mixed-Integer Linear Programming\",\"authors\":\"Michael R. Peabody\",\"doi\":\"10.1080/15366367.2022.2151081\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"ABSTRACT Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical representation of the test assembly problem that looks for the statistically optimal solution. Because MIP is a mathematical representation, changes to the test assembly problem typically involve only minor changes to the programming. This review focuses on comparing two free and open-source R packages for mixed integer linear programming: inlinelpSolveAPI and inlineompr. Programming style (with code provided), ease of use, run time, and other considerations will be examined. Solvers from other open-source platforms (e.g. Python, Julia) will also be discussed. Code and sample data are also provided.\",\"PeriodicalId\":46596,\"journal\":{\"name\":\"Measurement-Interdisciplinary Research and Perspectives\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.6000,\"publicationDate\":\"2023-01-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Measurement-Interdisciplinary Research and Perspectives\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1080/15366367.2022.2151081\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"SOCIAL SCIENCES, INTERDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Measurement-Interdisciplinary Research and Perspectives","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/15366367.2022.2151081","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SOCIAL SCIENCES, INTERDISCIPLINARY","Score":null,"Total":0}
Comparison of R Packages for Automated Test Assembly with Mixed-Integer Linear Programming
ABSTRACT Many organizations utilize some form of automation in the test assembly process; either fully algorithmic or heuristically constructed. However, one issue with heuristic models is that when the test assembly problem changes the entire model may need to be re-conceptualized and recoded. In contrast, mixed-integer programming (MIP) is a mathematical representation of the test assembly problem that looks for the statistically optimal solution. Because MIP is a mathematical representation, changes to the test assembly problem typically involve only minor changes to the programming. This review focuses on comparing two free and open-source R packages for mixed integer linear programming: inlinelpSolveAPI and inlineompr. Programming style (with code provided), ease of use, run time, and other considerations will be examined. Solvers from other open-source platforms (e.g. Python, Julia) will also be discussed. Code and sample data are also provided.