{"title":"关于估计队列性能缺陷的实际见解","authors":"J. Grayson, Todd Schultz","doi":"10.1504/IJIOME.2011.042664","DOIUrl":null,"url":null,"abstract":"Significant estimation errors, especially in high utilisation or low sample size situations, can occur when using sample data in standard queueing formulas to estimate queueing measures like time in queue. Perhaps surprisingly, these issues are rarely addressed, and especially in materials developed for students and practitioners. We establish error bounds in the case of exponential arrivals and Poisson service times for the single-server system when estimating average time in queue and also provide practical guidance for practitioners.","PeriodicalId":193538,"journal":{"name":"International Journal of Information and Operations Management Education","volume":"74 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Practical insights on pitfalls in estimating queue performance\",\"authors\":\"J. Grayson, Todd Schultz\",\"doi\":\"10.1504/IJIOME.2011.042664\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Significant estimation errors, especially in high utilisation or low sample size situations, can occur when using sample data in standard queueing formulas to estimate queueing measures like time in queue. Perhaps surprisingly, these issues are rarely addressed, and especially in materials developed for students and practitioners. We establish error bounds in the case of exponential arrivals and Poisson service times for the single-server system when estimating average time in queue and also provide practical guidance for practitioners.\",\"PeriodicalId\":193538,\"journal\":{\"name\":\"International Journal of Information and Operations Management Education\",\"volume\":\"74 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Information and Operations Management Education\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJIOME.2011.042664\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Information and Operations Management Education","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJIOME.2011.042664","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Practical insights on pitfalls in estimating queue performance
Significant estimation errors, especially in high utilisation or low sample size situations, can occur when using sample data in standard queueing formulas to estimate queueing measures like time in queue. Perhaps surprisingly, these issues are rarely addressed, and especially in materials developed for students and practitioners. We establish error bounds in the case of exponential arrivals and Poisson service times for the single-server system when estimating average time in queue and also provide practical guidance for practitioners.