报告题目：Robust Optimization for Sequential Investment Problems: An Application to Climate Adaptation in the Mississippi River Basin

报告所属学科：管理科学与工程

报告人：吴正稿（加拿大滑铁卢大学）

报告时间：2024年1月12日 15:00-18:30

报告地点：经管学院403室

报告摘要：

Effectively adapting to a changing climate involves making appropriate investment decisions based on long-term climate forecasts. This paper develops methods and performs a case study assessing how an investor would approach a long sequence of land investment decisions in the Mississippi River Basin (MRB) using popular climate models. Each of the 32 climate models is parameterized using an estimate of human greenhouse gas emissions, known as representative concentration pathways (RCP4.5 and RCP8.5), to generate a single climate forecast. Using a single climate forecast we generate a range of farmland values for the entire MRB. With the ranges we use a robust optimization model to determine the optimal investment policies given a desired level of conservatism, the extent to which farmland assets are constrained to adopt worst-case values. We show that the optimization model can be linearized and scales to large time frames, on the order of 50 plus years, and sets of assets. The case-study of investment in the MRB covers the years 2023-2090 and uses trajectories of land-values determined for each climate scenario using a regression model. We gather robust investment decisions from 32 individual climate models and the two RCPs. As the conservatism level increases, the range of latitudes over which investment takes place decreases and there are substantial differences in the regions where investment is optimal. Though all climate forecasts agree that on average the world is warming, our investment decisions show that the areas that benefit from the warming differ across models and RCP realizations. For the same RCP, across the 32 climate models we notice there may be investing in specific regions only, across regions, or even no investment at all. In general, our empirical analysis shows that there is disagreement between popular climate forecasts which influence land investment and may affect the most profitable land investments.

报告人简介：

吴正稿，加拿大滑铁卢大学管理科学与工程系的博士生，专门从事数据驱动的应用运营研究。2019年获南京航空航天大学管理科学与工程系硕士学位。他的研究兴趣包括不确定性应用运筹学、冲突解决图模型和决策科学。