随机优化是处理数据带有随机因素的一类优化问题。它是融概率统计、经典分析、数学优化于一体的研究领域。在经济、管理、工程以及生态等领域，随机优化在大数据时代有着广泛的应用。目前，随机优化理论主要用于处理带随机参数的各种模型：随机多目标模型、机会约束模型、两阶段和多阶段模型、分布鲁棒优化模型和随机变分不等式等。. 为进一步推动我国学者在随机优化领域的研究，申请者计划于2017 年9月20日--2016年10月8日在重庆师范大学为国内博士研究生和青年学者举办一个为期3周的专题高级讲习班，讲授三门与随机优化相关的课程，共68学时。

In the field of mathematical optimization, stochastic optimization is a framework for modeling optimization problems which involve uncertain data. It is a research field, which combines probability and statistics, classical analysis and mathematical programming. And, it is now being applied in a wide variety of areas including economics, management, mathematics, engineering, ecology, etc. Nowadays, stochastic programming theory offers a variety of models to address the presence of random data in optimization problems: chance-constrained models, two- and multi-stage models, distributionally robust optimization, stochastic variational inequalities. . In order to further promote the research of Chinese scholars in the field of stochastic programming, we plan to hold a 3-weeks’ senior workshop, on Sep 20-Oct 8, 2017, in Chongqing Normal University. And three with total 68 hours’ courses related to stochastic programming field will be given for graduate students and young scholars.