ESI 6912:

Introduction to Stochastic Optimization

Prof. STAN URYASEV

Course Syllabus




Class Website: http://www.ise.ufl.edu/esi6912/fall2007

Class Time: MWF 5 (11:45am-12:35pm)

Class Room: NSC 225

Text: John R. Birge and Francois Louveaux. "Introduction to Stochastic Programming". Springer, 1997. ISBN 0-387-98217-5

Instructor: Stan Uryasev

E-mail: uryasev@ufl.edu

Phone: (352) 392-1464 x 2023

Office: Weil 474;

Office Hours: Wednesday, 1:55-2:45 (7 period)

TA: Sergey Sarykalin

E-mail: saryk@ufl.edu

Phone: (352) 392-1464 ext. 2040

Office: Weil 473

Office Hours: Wednesday, 1:55-2:45 (7 period);  Friday, 12:50-1:40 (6 period)

Course Overview:
Introduction to Stochastic Optimization is intended as a first introductory course for graduate students in such fields as engineering, operations research, statistics, mathematics, and business administration (in particular, finance or management science). The objective of the course is to help students build knowledge and intuition in decision making under the presence of uncertainties, including:

  1. modeling of uncertainties;
  2. changes which uncertainties bring to the decision process;
  3. difficulties related to incorporation of uncertainties to optimization models;
  4. identifying of solvable problems.

The aim of stochastic programming techniques is to find an optimal decision in problems involving uncertainties and risks. The field, also known as optimization under uncertainty, is developing rapidly with contributions from many disciplines such as operations research, economics, statistics, and finance. Stochastic programming approaches have been successfully used in a number of areas such as energy and production planning, telecommunications, forest and fishery harvest management, engineering, agriculture, and transportation. Recently, it was realized that practical experience accumulated in stochastic programming can be expanded to much larger spectrum of applications including financial modeling, risk management, and probabilistic risk analysis.
This course is included in the list of required courses for the Co-major Financial Engineering/Mathematics program which is in the process of being set up at the University of Florida.

Course Topics:

  1. Various application examples: Financial Planning and Control, Capacity Expansion, Design for Manufacturing Quality, Rocket Design, Farming Planning, and Probabilistic Risk Analysis.
  2. Uncertainty and modeling issues (decisions and stages, two-stage programs, probabilistic programming, relationships to other decision-making models).
  3. Solution methods ( L-shaped method, stochastic quasi-gradient methods).
  4. Sensitivity analysis of stochastic systems (derivatives of expectations and probabilistic functions).
  5. Case studies.

Grading:

  1. Attendance -5%;
  2. Homework – 45%;
  3. Project - 40 % (see project requirements);
  4. Project review - 10%.

Absences and Late Arrivals:
Attendance will be taken. The final grade will be affected by frequent absences. Late arrivals will count as absences.

Prerequisites by Topic:
Some basic knowledge of calculus, statistics, and linear programming.

Honor Code:
Please note, and adhere to, the following policy. "We members of the University of Florida community, pledge to hold ourselves and our peers to the highest standards of honesty and integrity".