Asymptotically Optimal Policies for Dynamic Ambulance Dispatch

救护车动态调遣的渐进最优决策

Guest Speaker: Dr. Tong WANG (Shanghai Jiao Tong University)

Time/Date: 13:30 Thursday 29^th, June 2023

Classroom: Room 402, Tongji Building A

ABSTRACT:

We study the dynamic ambulance dispatch problem in emergency medical services, in which a decision-maker sequentially observes call arrivals and decides which unit to dispatch to service the call, where the service times follow independent and heterogeneous distributions for each station-location pair. This problem is formulated as a Markov decision process, which is intractable due to the curse of dimensionality. To solve this problem, we develop two easy-to-implement heuristics based on a deterministic linear program (LP) and the Lagrangian relaxation. We show that these policies have provably near-optimal performances as the number of units and arrival rates increase. We also show that the deterministic LP-based policy is still asymptotically optimal for general service time distributions. Finally, we examine the performance of these policies and the bounds on numerical experiments, including a case study based on real data from St. Paul, Minnesota. This is a joint work with Cheng Hua (SJTU), Jingwei Zhang (CUHK-SZ) and Ziyan Zhou (SJTU).

GUEST BIO

王彤，上海交通大学安泰经管学院副教授，主要研究方向包括随机建模与优化、随机动态规划、强化学习等，以及他们在供应链与库存管理、动态定价与收益管理、可持续运营管理等方向的应用。研究成果发表在Operations Research，Production and Operations Management等期刊，主持多项科研基金项目，包括国家自然科学基金优秀青年项目、上海市浦江人才计划项目等。