{"title":"高级教程:随机模拟中的输入不确定性和鲁棒分析","authors":"H. Lam","doi":"10.1109/WSC.2016.7822088","DOIUrl":null,"url":null,"abstract":"Input uncertainty refers to errors caused by a lack of complete knowledge about the probability distributions used to generate input variates in stochastic simulation. The quantification of input uncertainty is one of the central topics of interest and has been studied over the years among the simulation community. This tutorial overviews some methodological developments in two parts. The first part discusses major established statistical methods, while the second part discusses some recent results from a robust-optimization-based viewpoint and their comparisons to the established methods.","PeriodicalId":367269,"journal":{"name":"2016 Winter Simulation Conference (WSC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Advanced tutorial: Input uncertainty and robust analysis in stochastic simulation\",\"authors\":\"H. Lam\",\"doi\":\"10.1109/WSC.2016.7822088\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Input uncertainty refers to errors caused by a lack of complete knowledge about the probability distributions used to generate input variates in stochastic simulation. The quantification of input uncertainty is one of the central topics of interest and has been studied over the years among the simulation community. This tutorial overviews some methodological developments in two parts. The first part discusses major established statistical methods, while the second part discusses some recent results from a robust-optimization-based viewpoint and their comparisons to the established methods.\",\"PeriodicalId\":367269,\"journal\":{\"name\":\"2016 Winter Simulation Conference (WSC)\",\"volume\":\"24 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Winter Simulation Conference (WSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/WSC.2016.7822088\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Winter Simulation Conference (WSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WSC.2016.7822088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Advanced tutorial: Input uncertainty and robust analysis in stochastic simulation
Input uncertainty refers to errors caused by a lack of complete knowledge about the probability distributions used to generate input variates in stochastic simulation. The quantification of input uncertainty is one of the central topics of interest and has been studied over the years among the simulation community. This tutorial overviews some methodological developments in two parts. The first part discusses major established statistical methods, while the second part discusses some recent results from a robust-optimization-based viewpoint and their comparisons to the established methods.