Optimization in MATLAB: An Introduction to Quadratic Programming
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A control strategy for optimal operation of a hydroelectric dam is found through nonlinear and quadratic programming techniques. We use symbolic math to formulate an original model of the hydroelectric dam and then optimize the operation schedule using FMINCON. We then show how improvements can be made to the optimization process and end up with a quadratic programming problem that can be solved efficiently using the large-scale "interior-point-convex" algorithm with the QUADPROG solver.
These files go along with the "An Introduction to Quadratic Programming" webinar, which can be found here: http://www.mathworks.com/videos/optimization-in-matlab-an-introduction-to-quadratic-programming-81868.html
Comments and Ratings (12)
Updates
| 1.7.0.1 | Updated use of "sym" to clarify that variables are 'real'. |
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| 1.7.0.1 | Updated license |
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| 1.7.0.0 | Updated 3 files with copyright information |
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Jinwei Zhang (view profile)
Jinwei Zhang (view profile)
sensation (view profile)
Great work! One question, why beq is not equal to 90000 what is a final storage value? but instead to sum(inflow)? Thanks a lot!
Domenica Maria Conenna (view profile)
Jegvan hansen (view profile)
Leandro Coelho (view profile)
Hi,
You adopt the HydroelectricDamOptimization problem. Is there the description of this optimization problem in scientific papers and/or books?
Phillip Maser (view profile)
Its amazing how the tools work to generate answers to polynomial problems.
Wei Xiong (view profile)
dzu le ngoc (view profile)
thank you for Watching this File Optimization in MATLAB: An Introduction to Quadratic Programming.
Mohammad (view profile)
YuXiao (view profile)
Fabien (view profile)
Hi
great optimization problem and solution !
and very close to my job -> so i bought symobolic math toolbox and start to work on this example
I tried to adapt HydroelectricDamOptimization_largeScale to my problem (a 1 year problem with calculation every 8 hours)
and I ave some issues
some time the problem is not convex ! and i donc understand why
for example, in HydroelectricDamOptimization_largeScale we have MW2kW = 1000. with MW2kW = 1/1000, the probleme become non convex!
an idea why ? an idea to manage this issue ?
(this is just a stupid example, but I have this kind of issues when I try to adapt this exemple on real life)
thanks (and sorry for my poor english)
Fabien