CUTEr

CUTEr (Constrained and Unconstrained Testing Environment, revisited) is an open source testing environment for optimization and linear algebra solvers. CUTEr provides a collection of test problems along with a set of tools to help developers design, compare, and improve new and existing test problem solvers.

CUTEr is the successor of the original Constrained and Unconstrained Testing Environment (CUTE) of Bongartz, Conn, Gould and Toint.[1] It provides support for a larger number of platforms and operating systems as well as a more convenient optimization toolbox.

The test problems provided in CUTEr are written in Standard Input Format (SIF).[2] A decoder to convert from this format into well-defined subroutines and data files is available as a separate package. Once translated, these files may be manipulated to provide tools suitable for testing optimization packages. Ready-to-use interfaces to existing packages, such as IPOPT, MINOS, SNOPT, filterSQP, Knitro and more are provided. The problems in the CUTE subset are also available in the AMPL format. [3]

More than 1000 problems are available in the collection, including problems in:

Over time, the CUTEr test set has become the de facto standard benchmark for research and production-level optimization solvers, and is used and cited in numerous published research articles.

The SIF is a superset of the original MPS format for linear programming and of its extension QPS for quadratic programming. Therefore, access to problem collections such as the Netlib linear programs and the Maros and Meszaros convex quadratic programs is possible. Moreover, the collection covers the Argonne test set,[4] the Hock and Schittkowski collection,[5] the Dembo network problems, the Gould QPs, and others.

CUTEr is available on a variety of UNIX platforms, including Linux and Mac OS X and is designed to be accessible and easily manageable on heterogeneous networks.

References

  1. I. Bongartz, A.R. Conn, N. I. M. Gould and Ph. L. Toint, CUTE: Constrained and Unconstrained Testing Environment, ACM Transactions on Mathematical Software, 21:1, pp. 123-160, 1995.
  2. Standard Input Format (SIF)
  3. http://orfe.princeton.edu/~rvdb/ampl/nlmodels/cute/
  4. J. J. Moré, B. S. Garbow and K. E. Hillström, Testing Unconstrained Optimization Software, ACM Transactions on Mathematical Software, 7:1, pp 17-41, 1981.
  5. W. Hock and K. Schittkowski, Test Examples for Nonlinear Programming Codes, Lecture Notes in Economics and Mathematical Systems, Vol. 187, Springer 1981.
Notes
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