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        講座題目:Dynamic Stochastic Approximation for Multi-Stage Stochastic Optimization with Applications in Asset Allocation2019-06-14


        講座題目:Dynamic Stochastic Approximation for Multi-Stage Stochastic Optimization with Applications in Asset Allocation

        報告人:Prof. Guanghui (George) Lan, H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology

        講座時間:2019年6月25日(星期二)上午10:00-11:30

        講座地點:管理學院3樓313教室

        講座內容:In this talk, we first review some basic modeling techniques and solution methods for multi-stage stochastic optimization which has wide applications in operations management, such as inventory control and asset allocation. We then present a new stochastic first-order method, namely the dynamic stochastic approximation (DSA) algorithm, for solving these types of stochastic optimization problems. In particular, we show that DSA will be efficient in solving problems with a large number of decision variables, but a relatively small number of stages. We illustrate the advantages of this method over existing ones for solving a classic multi-stage asset allocation problem.

        學者介紹:Guanghui (George) Lan博士畢業于佐治亞理工學院(Georgia Institute of Technology),現為佐治亞理工學院副教授。主要研究方向為非線性規劃、隨機優化以及機器學習。他的研究成果在SIAM Journal on Optimization, Mathematical Programming, Journal of Computation Mathematics, Mathematical Programming等高水平期刊上發表。此外,Guanghui (George) Lan博士擔任Mathematical Programming, SIAM Journal on Optimization and Computational Optimization and Applications的副主編。

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