报告时间：2026年6月1日（星期一）16:30-17:30

报告地点：管理学院825会议室

报告人：代宏砚 教授

工作单位：中央财经大学

举办单位：合肥工业大学管理学院

报告简介：

With the continuous expansion of instant delivery platforms, public attention toward couriers has been growing, and both industry practitioners and academic researchers have attached greater importance to couriers’ income and working status including workload and psychological stress. Based on millions of real order data, this study verifies that while couriers seem to enjoy equitable income distribution, there exists hidden imbalance in actual delivery pressure. To address this issue, this paper proposes an efficiency-pressure collaborative aware scheduling framework. It constructs dual-dimensional pressure indicators consisting of average delivery urgency and work rhythm volatility, and develops a personalized scheduling optimization model embedded with pre-trained random forest to realize instant delivery scheduling that balances operational efficiency and couriers’ working pressure. Simulation results using real delivery data from Beijing show that the proposed strategy effectively reduces the overall pressure of couriers, narrows the pressure gap among couriers of different proficiency levels, and raises couriers’ income without lowering the delivery on-time rate. Compared with baseline methods, it achieves a better fairness-efficiency Pareto frontier performance.

报告人简介：

代宏砚，中央财经大学商学院教授、博士生导师，国家级青年人才入选者，中央财经大学管理研究中心主任。长期聚焦AI驱动智能决策，大模型人机协同机制，即时物流网络优化等前沿领域开展研究。近5年在《Management Science》等国内外顶级权威期刊发表高水平论文40余篇；主持国家自然科学基金重大研究计划培育项目、国家自然科学基金面上项目等4项国家级重点科研课题，先后斩获中国物流与采购联合会科技进步一等奖、浙江省科技进步三等奖，全球华人学者管理科学与工程年会管理科学实践奖二等奖，以及国际会议优秀论文一等奖等多项重磅学术与行业奖项。