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題名 Simulating Time-Varying Demand Services with Queuing Models
作者 郁方
Chu, Hsuan-Kai;Cheny, Wan-Ping;Yu, Fang
貢獻者 資管系
關鍵詞 Arrival rate estimation; Service simulation; Time-varying demands; Resource provision
日期 2016-05
上傳時間 6-Jun-2016 15:58:29 (UTC+8)
摘要 Resource provision for services that have timevarying demands has raised a great concern to service providers aiming at high-standard service quality. We propose a new resource provision approach using service simulation and arrival rate estimation that integrates unsupervised clustering and statistics techniques. We first cluster days that have similar arrival patterns together, where from each cluster we can reveal and separate days having different reasons for time-varying demands of the service. We then adopt the two layer business factor model to estimate multi-interval Poisson arrival distributions on daily bases for simulating stochastic processes. Applying simulation on queuing models with multi-interval Poisson arrival processes, we can observe stochastic changes of customer waiting time, queuing lengths and number of workers under different service strategies. We conduct a case study on an electricity service call center in real industries, showing how to build adequate resource provision and estimation against history data in past years and how the performance improved compared to their previous heuristics in real life operations.
關聯 the 13th IEEE International Conference on Services Computing, IEEE Service Society
資料類型 conference
dc.contributor 資管系
dc.creator (作者) 郁方zh_TW
dc.creator (作者) Chu, Hsuan-Kai;Cheny, Wan-Ping;Yu, Fang
dc.date (日期) 2016-05
dc.date.accessioned 6-Jun-2016 15:58:29 (UTC+8)-
dc.date.available 6-Jun-2016 15:58:29 (UTC+8)-
dc.date.issued (上傳時間) 6-Jun-2016 15:58:29 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/97705-
dc.description.abstract (摘要) Resource provision for services that have timevarying demands has raised a great concern to service providers aiming at high-standard service quality. We propose a new resource provision approach using service simulation and arrival rate estimation that integrates unsupervised clustering and statistics techniques. We first cluster days that have similar arrival patterns together, where from each cluster we can reveal and separate days having different reasons for time-varying demands of the service. We then adopt the two layer business factor model to estimate multi-interval Poisson arrival distributions on daily bases for simulating stochastic processes. Applying simulation on queuing models with multi-interval Poisson arrival processes, we can observe stochastic changes of customer waiting time, queuing lengths and number of workers under different service strategies. We conduct a case study on an electricity service call center in real industries, showing how to build adequate resource provision and estimation against history data in past years and how the performance improved compared to their previous heuristics in real life operations.
dc.format.extent 737724 bytes-
dc.format.mimetype application/pdf-
dc.relation (關聯) the 13th IEEE International Conference on Services Computing, IEEE Service Society
dc.subject (關鍵詞) Arrival rate estimation; Service simulation; Time-varying demands; Resource provision
dc.title (題名) Simulating Time-Varying Demand Services with Queuing Models
dc.type (資料類型) conference