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Queueing Analytics: Machine Learning, Causal Queueing, and SiMLQ for Data Driven Simulation

時間:2024-09-14來源:管理學院

報告時間2024年9月20日(星期五)10:00-11:30

報告地點:工程管理與智能制造研究中心825會議室

:Opher Baron   Distinguished Professor

工作單位University of Toronto(多倫多大學)

舉辦單位:管理學院

報告簡介

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.

報告人簡介

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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