Stochastic Optimization2011HT
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Course plan
No of lectures:
10
Recommended for
- doctoral students that have to or might in the future need to deal with
optimization problems.
- everyone who is or might be interested in an emerging field related to
mathematical programming.
The course was last given
New course.
Goals
The goal is to give an idea of how to handle uncertain parameters in an
optimization problem. More precisely, the aim is to give the participants an
introuction/overview of...
... why Stochastic Programming is an important extension of Mathematical
Programming.
... how optimization problems involving uncertain parameters can be modelled
mathematically.
... why Stochastic Programming is generally difficult and how to overcome some
of these difficulties.
... how (particular) Stochastic Programming Problems can be solved.
... examples of Stochastic Real-World Problems.
Prerequisites
Basic understanding of mathematical programming problems. Basic knowledge in stochastics.
Organization
The course should take place between 01/09/2011 and 31/12/2011.
The course will consist of 10 lectures ā 90min (a priori one lecture per week,
but this is flexible). After around half of the lectures the students receive a
subject to prepare a 10-15min presantation on. Some time will be given after
the last lecture for the students to prepare the exam (eg. 2 weeks).
Contents
- Different kinds of objectives in Stochastic Progranmming e.g. expected value
optimization, risk aversion, value-at-risk...
- Chance Constrained Programming
- Simple Recourse Problems
- Two- and Multi-Stage Programming
- Deterministic reformulation of stochastic programming problems
- Decomposition in stochastic programming
- Stochastic Decomposition
- Stochastic gradient algorithms
- Sample Average Approach
- Applications
Optional Contents:
- Related approaches like Robust Optimization and Dynamic Programming
- Approximation algorithms for Stochastic Combinatorial Optimization
- Metaheuristics for Stochastic Combinatorial Optimization
Literature
Lectures on Stochastic Programming (http://www2.isye.gatech.edu/people/faculty/Alex_Shapiro/SPbook.pdf) and others
Lecturers
Stefanie Kosuch
Examiner
Peter Jonsson
Examination
Oral exam (either individual or in small groups, depending on the number of
participants):
- 10-15min presentation of e.g. an article considering specific aspects
- Questions related to the presentation/article
- Questions related to the course content
Credit
5hp
Comments
Here you find slides on a guest lecture on Stochastic Combinatorial
Optimization that very briefly introduce some of the contents of this lecture:
http://www.kosuch.eu/en/stefanie/teaching/introsco.php
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