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Stochastic Optimization

2011HT

Status Archive
School Computer and Information Science (CIS)
Division TCSLAB
Owner Peter Jonsson

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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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