报告题目：Stochastic Robust Facility Location: A Nested Decomposition Approach

报告所属学科：管理科学与工程

报告人：王曙明（中国科学院大学）

报告时间：2023年5月18日 16:00-18:00

报告地点：经管学院702室

报告摘要：

In this work, we investigate a broad class of facility location problems in the context of adaptive robust stochastic optimization. A state-wise ambiguity set is employed to model the distributional uncertainty associated with the demand in different states, where the conditional distributional characteristics in each state are described by support, mean as well as dispersion measures, which are conic representable. A robust sensitivity analysis is performed in which on the one hand we analyze the impact of the change in ambiguity set parameters (e.g., state probabilities, mean value abounds and dispersion bounds in different states) onto the optimal worst-case expected total cost using the ambiguity dual variables. On the other hand, we analyze the impact of the change in location design onto the worst-case expected second-stage cost, and show that the sensitivity bounds are fully described as the worst-case expected shadow capacity cost. As for the solution approach, we propose a nested Benders decomposition algorithm for solving the model exactly, which leverages the subgradients of the worst-case expected second-stage cost at the location decisions formed insightfully by the associated worst-case distributions. The nested Benders decomposition approach ensures a finite-step convergence, which can also be regarded as an extension of the classic L-shaped algorithm for two-stage stochastic programming to our state-wise robust stochastic facility location problem with conic representable ambiguity. Finally, the results of a series of numerical experiments are presented which justify the value of the state-wise distributional information incorporated in our robust stochastic facility location model, the robustness of the model and the performance of the exact solution approach.

报告人简介：

中国科学院大学德赢官网下载王曙明教授，主要从事鲁棒优化与随机规划研究及其在选址与物流网络优化、供应链风险管理、库存与收益管理、健康医疗管理等领域的应用。研究成果分别发表于Production and Operations Management, INFORMS Journal on Computing, Transportation Science, IISE Transactions, Naval Research Logistics, IEEE Trans. Cybernetics等权威杂志上。目前担任运筹学著名期刊《Computers and Operations Research》的领域编辑(Area Editor).