报告题目：Optimal Staffing Strategies for Dynamic Queueing Systems with Two- Demand Patterns

报告时间：2024.11.20 16：30-17：30

报告地点：统计与数据科学学院 106

报告人简介：戴洪帅，山东财经大学统计与数学学院教授。2004年本科毕业于曲阜师范大学， 2010年博士毕业于中南大学，曾任加拿大卡尔顿大学及澳门大学博士后研究员。目前主要研究方向为排队系统理论及应用.

摘要：In this talk, we examine a dynamic queuing system characterized by two distinct demand patterns. We address an optimization problem focused on determining the optimal service capacities when arrival rates are piecewise stationary. Herein, we propose a batch online learning framework that integrates Stochastic Gradient Descent (SGD) algorithm with change point estimation techniques to address this dynamic optimization challenge. The effectiveness of our approach is substantiated by both theoretical analysis and simulation outcomes.