Fifth SIAM Conference on Optimization
SIAM Short Course 1
Sunday, May 19, 1996
Optimization: Algorithms, Software, and Environments
Victoria Conference Centre,
Victoria, British Columbia, Canada
Organizer: Jorge J. More, Argonne National Laboratory
This tutorial will provide a practical introduction to
mathematical programming languages, automatic differentiation tools, and recent advances in optimization technology. Mathematical programming languages, like AMPL and GAMS, greatly facilitate the formulation and solution of optimization problems, but many users are unaware of the power behind AMPL and GAMS. In addition, automatic differentiation tools, like ADIFOR and ADOLC, have made possible the efficient solution of problems that were not possible before. but many users feel that these tools are not applicable to their problems or too difficult to use. This tutorial will help users decide when and how to use these languages and tools. We will also provide a guided tour of the optimization technology available on the Web. Users of optimization will benefit by learning how the Web can help them solve their optimization problems.
Robert Fourer is a Professor in Northwestern University's Department of Industrial Engineering and Management Sciences. His professional interests include the study of optimization algorithms and the design of computer systems to support optimization. In collaboration with David Gay and Brian Kernighan of Bell Laboratories, he has designed a popular modeling language for optimization, and is co-author of the award-winning book AMPL: A Modeling Language for Mathematical Programming.
Jorge J. More‚ is a Senior Computer Scientist at Argonne National Laboratory. His research interests include the development and analysis of optimization software for large-scale problems. He has been actively promoting the use of problem solving environments and automatic differentiation tools for optimization, and is a co-author of the Optimization Software Guide (SIAM, 1993).
Stephen J. Wright is a Computer Scientist at Argonne National Laboratory.
His interests include interior-point methods, and applications of optimization in control and engineering. He is the author of a forthcoming book on interior-point methods and the co-author of a forthcoming text on numerical optimization.
Who Should Attend?
Staff of academic, government, and industrial institutions interested in learning how optimization technology can help them solve practical problems. Researchers in biology, chemistry, physics, and economics that need to know optimization techniques for their work.
A basic knowledge of computational linear algebra (Gaussian elimination, QR decomposition, Cholesky decomposition). Calculus for functions of several variables (Jacobians, gradients, Hessians). Working knowledge of a programming language (Fortran or C). Familiarity with the notation and techniques in the Optimization Software Guide (Part I only) (by Mor‚ and Wright, published by SIAM) is ample background.
Recent Developments in Algorithms and Software
- Linear programming software update
- Developments in simplex codes: steepest-edge becoming standard
Developments in interior point codes: the state-of-the-art
- Nonlinear programming software update
- Lancelot, SNOPT, other codes
Other areas: Mixed integer LP
- Software information on the Internet and WWW
- Home pages for existing software
Other resources and search tools
- Tools on the WWW
- NEOS Server
Mathematical Programming Modeling Languages
- Motivation: a simple example
- Matrix generators
Types of modeling languages
Algebraic modeling languages
- Problem types: linear, nonlinear, integer, network
Indexing: sets, compound sets, sets of sets
Implementing iterative schemes
- Uses in practice
- Solvers supported
Examples of large-scale applications
Environments and Automatic Differentiation
- Forward and reverse mode, complexity
ADIFOR and ADOLC: advantages and disadvantages
- Uses of automatic differentiation
- Optimization software
ELSO: An optimization environment
The NEOS Server
- Computing sparse Jacobian and Hessian matrices
Numerical results, accuracy, efficiency
- Computing gradients
- Partially separable functions
Forward and reverse modes
Numerical results, accuracy, efficiency
- Constraint logic programming
- Systems: Prolog based, object oriented
| ||Jorge More|
|9:00-10:30 ||Recent Developments in Algorithms and Software |
| ||Stephen Wright|
|11:00-12:30 ||Mathematical Programming Languages|
|(attendees are on their own for lunch)|
|2:00-3:00 ||Environments and Automatic Differentiation|
| || Jorge More|
|3:30-4:00 ||Environments and Automatic Differentiation (continued)|
|4:00-4:30 ||Constraint Logic Programming|
|4:30-5:00 ||Open discussion|
|5:00 ||Short Course adjourns|
Registration Fees (for either Short Course)
|SIAG/Opt Member*|| SIAM Member||Non-Member||Student|
|Preregistration (before 5/6/96)||$110||$110||$125 ||$40|
|Registration (after 5/6/96) ||$125 ||$125 ||$140 ||$55 |
*Member of SIAM Activity Group on Optimization.
Short Course fees include course notes and refreshment breaks.
To register for either short course, the conference, or both, please fill-in and submit the preregistration form.
On-site registration will start on Saturday, May 18 at 6:00 PM at the entrance, Lobby Level of the Conference Centre.
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