报告题目：Stochastic Mixed-Integer Programming for Natural Disaster Relief

报告所属学科：管理科学与工程

报告人：杨浩翔（香港中文大学（深圳））

报告时间：2023年11月16日 14:00-17:00

报告地点：威尼斯wns·8885566702室

报告摘要：

Stochastic optimization is an effective approach for modeling decision-making in natural disaster relief operations, particularly when faced with stochastic disruptions. In this talk, we discuss two specific application examples of infrastructure operations under natural disasters. The first example addresses the integrated protection and restoration of interdependent infrastructure networks. In the formulated two-stage stochastic program under disruption, the first stage focuses on the decisions regarding fortification of components, while the second stage considers repair crew schedules and network flow. The second example considers the preemptive shutoffs and power flow operations of an electric power system under wildfire uncertainty. The occurrence of the wildfire is also uncertainty, which motivates us to construct a two-stage stochastic mixed-integer program, where the recourse problem may have a random length. We show that in spite of non-convex recourse problems, both problems can be solved exactly by cutting-plane algorithms, featuring novel variants of Lagrangian cuts, and we will demonstrate the efficacy of such algorithms.

报告人简介：

杨浩翔博士毕业于美国西北大学，现任职于香港中文大学（深圳），担任数据学院助理教授，博士生导师。杨浩翔博士主要研究领域为不确定优化，尤其聚焦随机优化、鲁棒优化、整数规划和非线性优化，主要应用场景为能源系统、物流和供应链、灾难援救和运动分析等。杨浩翔博士近年在国际著名学术期刊发表多项研究成果，期刊包括Mathematical Programming、 INFORMS Journal on Computing、SIAM Journal on Optimization、Nature Communications等。