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Queueing Analytics: Machine Learning, Causal Queueing, and SiMLQ for Data Driven Simulation
发布日期:2024-09-14  来源:   查看次数:

报告时间:2024年9月20日(星期五)上午10:00-11:30

报告地点:工程管理与智能制造研究中心825会议室

人:Opher Baron

工作单位:University of Toronto(多伦多大学)

举办单位:合肥工业大学管理学院

报告简介:

The objective of this talk is to expose researchers to the vast possibilities of using modern machinery and data for implementing effective management analytics for processes that can be modeled as queueing systems. Such process are ubiquitous in modern economies, e.g., customers waiting to service, inventory waiting for processing/transportation, payments and invoices waiting to be generated/cleared, computing tasks waiting for resources. I will thus discuss recent developments in queueing analysis based on several papers.

报告人简介:

Opher Baron is a Distinguished Professor of Operations Management at the Rotman School of Management, University of Toronto. He serves as an associate editor for several prestigious journals, including Operations Research, Manufacturing & Service Operations Management, Mathematical Methods of Operations Research, and Service Science. His research interests encompass queueing theory, business analytics, service operations (such as healthcare), autonomous vehicles, and revenue management. Opher's work has been published in leading journals such as Operations Research, Management Science, Manufacturing & Service Operations Management, Production and Operations Management, and Mathematical Methods of Operations Research. He has also received several research and teaching awards and grants.

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