12
$\begingroup$

I am looking for (sources of) convex quadratic programming instances with linear constraints. I am open for both continuous and mixed integer problems, but do not want randomly generated instances.

I am aware of QPLIB, a collection of various types of convex/noncovex, integer/continuous, linearly constrained/quadratically constrained quadratic programmes.

I am also aware of the Maros and Meszaros test set.

$\endgroup$
  • 2
    $\begingroup$ Maybe this deserves a [test-instances] tag? $\endgroup$ – LarrySnyder610 May 31 '19 at 16:53
  • $\begingroup$ yes I was wondering how the tag should be named, [testset], [test-instances], [benchmarks].. $\endgroup$ – Michael Feldmeier May 31 '19 at 16:54
  • 2
    $\begingroup$ Seems like you're the first one to need it, so I guess you get to decide. :) $\endgroup$ – LarrySnyder610 May 31 '19 at 16:55
11
$\begingroup$

There are at least three more problem libraries that you can access.

  1. OR-Lib has instances of Quadratic Assignment/Knapsack/Minimum spanning tree that you can use.
  2. MINLP-Lib has several QP, BQP, IQP instances that you can filter by convexity.
  3. PrincetonLib chapter 2 problems.

I think that you can apart of it come up with synthetic instances which are not completely random (you provide certain structure) easily, like Quadratic assignment problems.

| improve this answer | |
$\endgroup$
  • 1
    $\begingroup$ Thanks! I think all the problems in PrincetonLib Chapter 2 are nonconvex. QAP usually is nonconvex as well, but OR-Lib also seems to have portfolio rebalancing/optimization instances, which might be convex. MINLP-Lib has some overlap with QPLIB, but there are some more in there. $\endgroup$ – Michael Feldmeier Jun 1 '19 at 8:51
8
$\begingroup$

You can reformulate Quadratic Programs as Second Order Conic Programs (SOCPs). Therefore, you can use many conic benchmark libraries and filter SOCPs.

For example, Conic Benchmark Library can be a good start!

| improve this answer | |
$\endgroup$
  • 2
    $\begingroup$ But not every SOCP can be reformulated as a convex QP with linear constraints, right? My question aims at the situation of having a new solver for convex, linearly constrained QP and wanting to test it with as many problem instances as possible. $\endgroup$ – Michael Feldmeier May 31 '19 at 17:49
  • 1
    $\begingroup$ Yes, i mean you can find the linearly constrained qp's. I am looking if there is a general library for what you look for. $\endgroup$ – independentvariable May 31 '19 at 18:21

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.