Graduate Course in Optimization
John Hedengren
We'll start the first online session today at 4 PM MST for the graduate course in optimization. You can log-on to the WebEx session here:
https://byu.webex.com/mw0306ld/mywebex/default.do?siteurl=byu
Password: me575
Today, we'll discuss an optimization problem on the design of a Two Bar Truss including techniques for modeling that allow improved solver convergence.
http://apmonitor.com/me575/index.php/Main/TwoBarTruss
I've pre-recorded some of the class material so that you can watch beforehand. You are welcome to use any platform of your choice for solving optimization problems. The tutorials are provided in MATLAB and Python with the APM modeling extension.
http://www.youtube.com/playlist?list=PLLBUgWXdTBDgGKXygRKKEZMUhsqPmhd_G
The first part of the course is focused on solving engineering problems and is meant to teach students about optimization software. The second part of the course covers theory related to algorithm design. The final part of the course is a project that can be a project of your choice, preferably related to your research.
Upcoming or prior activities include:
We’ve started by running through some optimization basics and tutorial examples:
http://apmonitor.com/me575/index.php/Main/OptimizationBasics
The next few assignments are engineering design problems:
http://apmonitor.com/me575/index.php/Main/SpringDesign
heat integration…
http://apmonitor.com/me575/index.php/Main/MilkPasteurization
pumping optimization…
http://apmonitor.com/me575/index.php/Main/LimestoneSlurry
thermodynamic parameter estimation…
http://apmonitor.com/me575/index.php/Main/VLEWilson
kinetic modeling and dynamic parameter estimation…
http://apmonitor.com/me575/index.php/Main/KineticModeling
I look forward to your involvement. The online session is actually right after the normally scheduled class but I'll be recording much of the lecture material so that you can view it at your convenience. The WebEx sessions are meant to be collaborative work-sessions with a strong hands-on component. Please let me know if you have any questions.
Best regards,
John Hedengren
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I'd like to invite anyone who is interested to participate in a graduate-level course on Optimization Techniques in Engineering. The course uses IPOPT as one of the solvers embedded in MATLAB and Python for tutorials and homework problems. There is no charge for course participation, and industrial and academic participants are freely welcome. The graduate course at BYU has 60 students from Chemical, Civil, Electrical, and Mechanical engineering.
Course Topics
We cover theory and applications of constrained, unconstrained, continuous, and discrete problems and address problems in linear programming, quadratic programming, integer programming, nonlinear optimization, systems of dynamic nonlinear equations, and multiobjective optimization. The activities include searching for optimal solutions, performing tradeoff analyses, balancing multiple design alternatives, and developing optimization methods into comprehensive modeling and analysis solutions.
Ways to be involved
We are also interested in participants who can help share their experience with optimization. This may include giving guest lectures, participating in help sessions, or sponsoring a student course project.
The course web-site is located at http://apmonitor.com/me575 and has lecture notes, YouTube videos, and interactive discussion forums. Please fill out an information sheet (see Info Sheet link on the right) to tell me a little more about your interests with the course or send me an e-mail at john.he...@byu.edu. The course discussion sessions are hosted with WebEx and are held every Monday, Wednesday, and Friday from 4-5 PM MST. The password for joining the discussion session is me575.
John Hedengren
Assistant Professor
Department of Chemical Engineering
Brigham Young University