Transcription of Introduction to Stochastic Optimization - ise.ufl.edu
1 Introduction to Stochastic Optimization , ESI 6341 Page 1 Prof. Stan Uryasev, Fall 2018 Introduction to Stochastic Optimization ESI 6341 Section 2717 Class Periods: MWF, period 6 (12:50 PM - 1:40 PM) Location: LAR 0239 Academic Term: Fall 2018 Instructor: Stan Uryasev (352) 213-3457 (cell) Office Hours: Weil 446, TBD Teaching Assistants: Please contact through the Canvas website Charles Hernandez Office Hours: Weil 406, TBD Course Description (3 credits) 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). Course Pre-Requisites / Co-Requisites Basic knowledge of calculus, statistics, and linear programming. Course Objectives 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.
2 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, has 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. Materials and Supply Fees None Required Textbooks and Software a. Title: Introduction to Stochastic Programming b. Authors: John R. Birge and Francois Louveaux c. Publication date and edition: Springer, 2011 d.
3 ISBN number: 978-1-4614-0236-7 Introduction to Stochastic Optimization , ESI 6341 Page 2 Prof. Stan Uryasev, Fall 2018 Recommended Materials None Course Schedule The course schedule is offered as a general guide. Delivery dates of homeworks and projects are posted at the class website. Week Lesson Homework/Project 1 Introduction 2 Basic concepts of Stochastic programming (explained with farming problem) 3 Financial planning 4 Design for manufacturing quality 5 Capacity expansion model (electricity generation) Homework 1 6 Summary of examples with recourse formulation 7 VaR and CVaR: algorithms and applications 8 Two stage problems: theoretical statements 9 Probabilistic or chance constraints Homework 2 10 Fundamental quadrangle of risk in Optimization and statistics 11 Fundamental quadrangle: explanations and examples 12 Examples of applications Project draft 13 Presentation of projects Project 14 Presentation of projects Project 15 Presentation of projects Project 16 Presentation of projects Project Attendance Policy, Class Expectations, and Make-Up Policy You get up to 5% of grade for attending the class (proportional to the number of attended classes).
4 Late arrivals will count as absences. Homework problems will be assigned in the beginning of each section. Late homework will not be accepted. Excused absences are consistent with university policies in the undergraduate catalog ( ) and require appropriate documentation. Cell phones should be turned off during classes. Evaluation of Grades Assignment Total Points Percentage of Final Grade Attendance 5% Homeworks (2) 100 each 45% Project 100 40% Project review 100 10% 100% Grading Policy Percent Grade Grade Points - 100 A - A- - B+ - B Introduction to Stochastic Optimization , ESI 6341 Page 3 Prof. Stan Uryasev, Fall 2018 - B- - C+ - C - C- - D+ - D - D- 0 - E More information on UF grading policy may be found at: Students Requiring Accommodations Students with disabilities requesting accommodations should first register with the Disability Resource Center (352-392-8565, ) by providing appropriate documentation.
5 Once registered, students will receive an accommodation letter which must be presented to the instructor when requesting accommodation. Students with disabilities should follow this procedure as early as possible in the semester. Course Evaluation Students are expected to provide feedback on the quality of instruction in this course by completing online evaluations at Evaluations are typically open during the last two or three weeks of the semester, but students will be given specific times when they are open. Summary results of these assessments are available to students at University Honesty Policy UF students are bound by The Honor Pledge which states, We, the members of the University of Florida community, pledge to hold ourselves and our peers to the highest standards of honor and integrity by abiding by the Honor Code. On all work submitted for credit by students at the University of Florida, the following pledge is either required or implied: On my honor, I have neither given nor received unauthorized aid in doing this assignment.
6 The Honor Code ( ) specifies a number of behaviors that are in violation of this code and the possible sanctions. Furthermore, you are obligated to report any condition that facilitates academic misconduct to appropriate personnel. If you have any questions or concerns, please consult with the instructor or TAs in this class. Campus Resources: Health and Wellness U Matter, We Care: If you or a friend is in distress, please contact or 352 392-1575 so that a team member can reach out to the student. Counseling and Wellness Center: , and 392-1575; and the University Police Department: 392-1111 or 9-1-1 for emergencies. Sexual Assault Recovery Services (SARS) Student Health Care Center, 392-1161. University Police Department at 392-1111 (or 9-1-1 for emergencies), or Academic Resources Introduction to Stochastic Optimization , ESI 6341 Page 4 Prof. Stan Uryasev, Fall 2018 E-learning technical support, 352-392-4357 (select option 2) or e-mail to Career Resource Center, Reitz Union, 392-1601.
7 Career assistance and counseling. Library Support, Various ways to receive assistance with respect to using the libraries or finding resources. Teaching Center, Broward Hall, 392-2010 or 392-6420. General study skills and tutoring. Writing Studio, 302 Tigert Hall, 846-1138. Help brainstorming, formatting, and writing papers. Student Complaints Campus: On-Line Students Complaints.
