MSC 380.8, ORI 391Q.1 - NONLINEAR PROGRAMMING

UNIQUE NUMBER: 04075, 17910

CLASS MEETINGS
Fall 2001

PROFESSOR:
Leon S. Lasdon
Office: CBA North 5.244
Phone: 471-9433
Email: lasdon@mail.utexas.edu

CLASS WEB PAGE:
http://www.utexas.edu/courses/lasdon/

OFFICE HOURS:
MW 1-2:30, TTh 11-12, or by appointment

TEACHING ASSISTANT:
Xiangtong Qi
Email: qix@mail.utexas.edu Office: CBA 1.306C
Office Hours: W 1:30-2:30, Th 3:30-4:30

REQUIRED TEXT:
Linear And Nonlinear Programming, S. Nash and A. Sofer, McGraw-Hill, 1996.

ADDITIONAL REFERENCES:
Supplementary Readings: Readings packet at Paradigm Publishing, corner of 24th St. near Guadalupe.

WEBSITES: This year's syllabus and last year's session plans are available at www.utexas.edu/courses/lasdon. You will also visit several optimization websites as part of this class, and will be asked to report on what you found in the next class. Some of these sites are:

1. www.frontsys.com. This is the Frontline Systems website. Frontline and Lasdon jointly developed the Excel Solver, and Frontline markets enhanced Solvers for Excel.
2. www.optimalmethods.com. This is the Optimal Methods website, which markets NLP software.
3. www.modeling.com. This is the COMPASS Modeling Solutions Website. One of their products is AMPL+, which is a leading algebraic modeling language for optimization.
4. plato.la.asu.edu/guide.html. This is a site developed by Hans Mittlemann at Arizona State University and P. Spellucci of Technical University Darmstadt. It contains much info on a broad range of optimization topics. It contains links to many other sites and downloadable software and papers.
5. http://www.ece.northwestern.edu/OTC/. This is the website of the Optimization Technology Center at Argonne National Laboratories. It contains much information, plus software. It also allows you to submit an optimization problem to them and get a solution. See readings for more information.
6. www.gams.com. This is the GAMS Development Corporation website. GAMS is another widely used algebraic modeling language for optimization, which we will use in this course.
7. www.ampl.com. This is another AMPL site.

See the readings packet, readings 3, for listings of the first page of some optimization websites.

EXAMS:
Midterm Take-home
Final (70% project, 30% in-class final)

GRADING:
Midterm Exam 1/3, Final Exam 1/3, Homework and Cases 1/3.

INSTRUCTIONAL METHODS:
The basic approach is to learn by doing. We will organize small learning groups, who work together to solve problems in class. These problems are stated on the plan for each class. Last years plans are on the course website, and are a reasonable guide to those used in the current year. We then discuss the problem solutions. This is interspersed with lecture segments when needed. There will also be occasional outside speakers, who will explain how they use course topics in their work.

COURSE DESCRIPTION:

1. Theory: Understand the derivation and uses of the Kuhn-Tucker first order necessary conditions for optimality, second order optimality conditions, saddle points, and the Lagrangian dual problem. Also, understand basic convexity results, and convergence and rate of convergence results for various algorithms.
2. Algorithms: Understand the derivation and comparative advantages of the following classes of algorithms (Use given implementations of these algorithms, observe and analyze the results.):
1. Generalized Reduced Gradient (GRG)
2. Successive Quadratic Programming (SQP)
3. Successive Linear Programming (SLP)
4. Penalty and Barrier Methods, Exact and Inexact
5. Interior Point Methods.
3. Applications:
1. Learn to use stand-alone Fortran or C NLP solvers to solve problems coded in Fortran or C.
2. Learn to use the Excel Solver and GAMS.
3. Understand the relative advantages and limitations of the above tools.
4. Learn about several important current NLP application areas, including:
1. gasoline blending, refinery models
2. electric power: hydroelectric planning, optimal load flows
3. financial applications: Markowitz asset allocation, multiperiod models, robust optimization
4. optimal control
5. water resources models
6. others of interest to the class
5. Improve your skills as a modeler by formulating a variety of problems in several modeling languages, solving, and analyzing and understanding the solution. Learn principles of good modeling as well as things to avoid.

STUDENTS WITH DISABILITIES:
The University of Texas at Austin provides upon request appropriate academic adjustments for qualified students with disabilities. For more information, contact the Office of the Dean of Students at 471-6259, 471-4241 TDD or the Cockrell School of Engineering Director of Students with Disabilities at 471-4382.

COURSE EVALUATION:
Near the end of the course you will have an opportunity to anonymously evaluate the course and instructor using the standard Cockrell School of Engineering evaluation form.

 

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