YALMIP forum on Google Groups

Questions and discussions on YALMIP and related optimization modelling issues are now handled using Google groups.

Hope to see you at the YALMIP Q/A forum!.

Release 20141218

Minor release with some small fixes.

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Release 20141127

The previous version had some configuration issues which caused some of the fixes to get lost. Hence, this release includes the fixes announced in the previous release and some additional fixes related to scs.

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Release 20141125

This release fixes some minor issues and fixes a warning occurring after upgrading to Gurobi 6.0.

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Release 20141030

This release fixes some minor issues and adds support for the solver SCS.

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Release 20140915

This release fixes numerous small issues and adds support for the semidefinite programming presolver frlib developed by Frank Permenter and Pablo Parrilo. It also features some internal changes which could break old(-style) code.

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Release 20140619

This release fixes some small issues, and runs in Octave.

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Octave support

I have been asked several times if I would consider an Octave port. My answer has been no, based on my, as it turns out, flawed idea that it would require a lot of changes (and my general lack of interest in Octave). Well, yet another request came, and I decided to download Octave and test it. Turned out the changes required were absolutely minimal. Hence, as of now, YALMIP runs in both MATLAB and Octave.

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Release 20140605

Minor release fixing some small issues.

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Release 20140221

Minor release fixing an issue with optimizer introduced in the latest release.

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Release 20140217

Minor release with new solvers, bug-fixes and performance tweaks.

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Release 20131220

Minor release with new solvers and various bug-fixes.

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Release 20131002

Minor release.

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Release 20130628

Minor release.

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YALMIP and Simulink

I have been asked frequently recently whether is is possible to have YALMIP code in Simulink simulations. The answer is yes, but there are some caveats.

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Release 20130405

Required release if you use MATLAB R2013a.

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Release 20130322

Required release if you use MATLAB R2013a.

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Release 20130213

Minor release with some small enhancements and, for the first time in 10 years probably, support for a new SDP solver.

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Release 20130201

Minor release.

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Unit commitment example

A common application of integer programming is the unit commitment problem in power generation, i.e., scheduling of set of power plants in order to meet a current and forecasted power demand while minimizing costs.

To see how such a problem is modeled in YALMIP, a unit commitment example is now available.

If you would like to see how additional constraints or logic behaviour can be added to the model, let me know!

Release 20130128

Minor release fixing an issue in the CPLEX interface.

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Release 20130124

Minor release fixing some small issues. If you use CPLEX, you should update.

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Beta version of a more general optimizer command

The command optimizer is used to reduce overhead when solving a large number of optimization problems which only differ through some changing parameter in the model. Previously, this feature has been limited to models where the changing parameter has entered the model affinely. Read more...

Release 20130111

Minor release fixing some small issues.

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Release 20131002

Minor release.

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Prepare your code for the future!

In coming versions of YALMIP, the operators > and < will not be allowed in constraints. Hence, to prepare, you should replace occurrences of these operators with <= and >=.

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Release 20111128

Important release. A massive performance degradation was accidentally added to the two most recent releases. Hence, the latest release should be installed.

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Solving nonconvex QPs

A common question I get is along the lines "how can I solve a nonconvex QP using SeDuMi"

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Strictly feasible sum-of-squares solutions

A question on the YALMIP forum on the SeDuMi homepage essentially boiled down to "how can I generate sum-of-squares solutions which really are feasible, i.e. true certificates" Read more...

Worst-case matrix norm

I was asked by a colleague today on how to compute the worst-case ∞-norm of a matrix A(p) linearly parameterized in an uncertainty p constrained to a polytope. Read more...

Robust optimization paper

A paper describing the robust optimization module has been accepted for publication.

Convex Algebraic Geometry

Philipp Rostalski has made his Convex Algebraic Geometry Wiki public. Among other things, you can find the tool Bermeja, which is partly based on YALMIP.

Polytopic geometry using YALMIP and MPT

Ever wondered how to compute the L1 Chebyshev ball? Check out the new article on polytopic geometry using YALMIP and MPT

Swedish control conference mini-course material

Material from the mini-course on YALMIP and MPT for Optimization and Modelling in Control at the Swedish control meeting is now available for download. Please note that you need the latest release to run some of the examples.

Note: The code is slightly outdated as it uses the command solvesdp instead of optimize, and double instead of value.

CPLEX 12

CPLEX 12, which now is shipped with MATLAB support, is now supported in YALMIP.

Gurobi

I am very pleased to announce that YALMIP now supports the mixed-integer linear programming solver Gurobi. The solver is interfaced via Gurobi mex developed by Wotao Yin.

Pre-processing sum-of-squares

A new sum-of-squares example has been made available. This example concentrates on the pre-processing capabilities of YALMIPs sum-of-squares module.

Robust optimization poster and paper

A poster and a related paper (Löfberg:2008b) presenting the robust optimization module has been uploaded to the Wiki.