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Applied Mathematics & Statistics, and Scientific Computation

BMGT808E Stochastic Optimization

To AMSC Students:

asdf I am pleased to announce BMGT808E, "Stochastic Optimization," a new Ph.D. course offered by the Operations Management group at the Smith School of Business. This course, taught for the first time in Fall 2012, provides a survey of models and methods used for solving cutting-edge problems in stochastic optimization. I would like to reach out to AMSC students who are interested in incorporating decision-making under uncertainty into their research.

The objective of the course is to provide a broad perspective of this interdisciplinary field, bringing together viewpoints from such communities as operations research, civil engineering, computer science, and simulation. Attached is a PDF of the tentative syllabus for the course. Topics covered include stochastic search, dynamic programming, stochastic programming, and the emerging discipline of optimal learning. The class may also feature guest speakers on cutting-edge research in stochastic optimization. We will focus on usable methods that can be, and have been, successfully implemented to solve practical applications in transportation, operations management, health care, and energy.

The workload will consist of 4-5 homework assignments to be handed in roughly once every two weeks. There will be one in-class midterm exam. There will be no final exam, but there will be a course project which will require students to model a stochastic optimization problem and attempt to solve it using one or more techniques from class. There is no set topic for the project -- it is my hope that students will bring applications from their own area of expertise, and use the project to begin integrating stochastic optimization into their research. Most of the homework will be assigned in the first half of the semester, thus freeing up time for students to work on their projects in the second half.

The only pre-requisite for BMGT808E is any graduate-level course in probability and stochastic processes at the level of BMGT834, or an equivalent course from another program. It is not necessary to have a background in measure theory for this course. If you are unsure about your background, please discuss the matter with me.

My tentative meeting time for the course is Thursdays, 3:30-6:10 PM. However, if enough students ask for a different time, it may be changed. If you are interested in the course, I would appreciate it if you could answer a few quick questions on this form:

I look forward to seeing you in BMGT808E this fall.

Ilya O. Ryzhov
Assistant Professor
Robert H. Smith School of Business

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Ilya O. Ryzhov
Assistant Professor
Department of Decision, Operations and Information Technologies
Robert H. Smith School of Business
4322 Van Munching Hall
University of Maryland
College Park, MD 20742-1815
(301) 405-1118 TEL