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光华讲坛—鲁棒与随机优化系列讲座(十三): Robust Stochastic Optimization Made Easier in Python
发布时间: 2021-07-19

主题:鲁棒与随机优化系列讲座(十三): Robust Stochastic Optimization Made Easier in Python

主讲人 香港城市大学 陈植助理教授

主持人 工商管理学院 徐亮教授

时间: 2021年7月23日(周五)15:00-16:00

举办地点 腾讯会议, 会议ID:776 374 609

主办单位 工商管理学院 科研处


Zhi Chen is an Assistant Professor in the Department of Management Sciences, College of Business, City University of Hong Kong. His research interests include (1) decision-making under uncertainty with different levels of data availability and its applications in decision analysis, operations management, and engineering; (2) cooperative game theory for joint activities and its applications in production economics, resource pooling, and risk management. His works appear in leading journals such as Management Science, Operations Research, Mathematical Finance, and Transportation Science.

陈植博士是香港城市大学商学院管理科学系助理教授,研究兴趣包括:(1)不同数据可用性水平下的不确定性决策及其在决策分析、运营管理和工程中的应用;(2)联合活动的合作博弈论及其在生产经济学、资源池和风险管理中的应用。陈植博士在运筹学权威期刊,如Management Science, Operations Research, Mathematical Finance, and Transportation Science等,发表过多篇文章。


In this paper we introduce a Python package called RSOME for modeling a wide spectrum of robust and distributionally robust optimization problems. RSOME serves as an open-source platform for modeling various optimization problems subject to distributional ambiguity in a highly readable and mathematically intuitive manner. It is versatile and well fits in the open-source software community, in the sense that (i) it is consistent with NumPy arrays in indexing and slicing, as well as array operations; (ii) together with the rich Python libraries for machine learning, data analysis and visualization, it is easier to implement data-driven models; and (iii) it provides convenient interfaces for users to switch and tune parameters among different solvers.